JP4362290B2 - Haplotype analysis apparatus and program for causing computer to execute haplotype analysis method - Google Patents

Description

【０１３５】
なお、上記数式１のＬｃａｓｅ、Ｌｃｏｎｔｒｏｌ、Ｌｃａｓｅ＋ｃｏｎｔｒｏｌの各値は、それぞれ，ケースコントロール分類結果ファイル１０６ｂに格納されているケースコントロール分類結果を基に、連鎖不平衡部位検定部１０２ｅが計算した、ケース（患者）集団、コントロール（健常者）集団、ケースとコントロールをあわせた集団に対する尤度である。
【０１３６】
再び図１６に戻り、ハプロタイプ解析装置１００は、連鎖不平衡部位検定部１０２ｅの処理により、ＬＲ（Ｔ５）の帰無仮説下分布を求める（ステップＳＣ−３）。
【０１３７】
ついで、ハプロタイプ解析装置１００は、連鎖不平衡部位検定部１０２ｅの処理により、実際のＳＮＰサンプルデータからハプロタイプ頻度をケース、コントロール、ケース＋コントロールごとに予想し、ＬＲ（Ｔ５）を計算する（ステップＳＣ−４）。
【０１３８】
ついで、ハプロタイプ解析装置１００は、連鎖不平衡部位検定部１０２ｅの処理により、ステップＳＣ−４の処理により得られたＬＲ（Ｔ５）がステップＳＣ−３の処理により求められた分布から充分偏っていることを確認した上で、帰無仮説を棄却する（ステップＳＣ−５）。
【０１３９】
ついで、ハプロタイプ解析装置１００は、連鎖不平衡部位検定部１０２ｅの処理により、指定された回数分、ステップＳＣ−１からステップＳＣ−５の処理を繰り返してパーミュテーションテストを行う（ステップＳＣ−６）。
【０１４０】
具体的には、連鎖不平衡部位検定部１０２ｅは、まず当該指定された回数を連鎖不平衡部位検定結果ファイル１０６ｇの「Ｎｕｍ」に格納し、そして、パーミュテーションテストを実行し、当該パーミュテーションテストの結果、ある尤度以上の値が得られた回数を連鎖不平衡部位検定結果ファイル１０６ｇの「Ｒｅａｃｈ」に格納する。
【０１４１】
さらに、ハプロタイプ解析装置１００は、連鎖不平衡部位検定部１０２ｅの処理により、ＬＲ（Ｔ５）のシミュレーションに基づくＰ値（ｅｍｐｉｒｉｃａｌＰ）を計算し、連鎖不平衡部位検定結果ファイル１０６ｇの「ｅｍｐＰ」の項に格納する（ステップＳＣ−７）。
【０１４２】
これにて、遺伝的異質性検定処理が終了する。
【０１４３】
再び図１４に戻り、ハプロタイプ解析装置１００は、制御部１０２の処理により、ステップＳＡ−２からステップＳＡ−５の処理をすべてのＬＤブロックに対して適用する（ステップＳＡ−６）。
【０１４４】
ついで、ハプロタイプ解析装置１００は、ＳＮＰ検定部１０２ｆの処理により、すべてのＳＮＰに対して、ステップＳＡ−５と同様に遺伝的異質性の検定を行い、当該遺伝的異質性の検定の結果をＳＮＰ検定結果ファイル１０６ｈの所定の領域に格納する（ステップＳＡ−７）。
【０１４５】
なお、ＳＮＰ検定部１０２ｆにて行われる遺伝的異質性の検定は、連鎖不平衡部位検定部１０２ｅにて行われる上述した遺伝的異質性検定処理に対応するため、説明は省略する。
【０１４６】
さらに、ハプロタイプ解析装置１００は、比較分析部１０２ｇの処理により、ステップＳＡ−５の検定結果とステップＳＡ−７の検定結果を比較分析し、当該比較分析の結果を比較分析結果ファイル１０６ｉの所定の領域に格納する（ステップＳＡ−８）。
【０１４７】
具体的には、比較分析部１０２ｇは、連鎖不平衡部位検定結果ファイル１０６ｇとＳＮＰ検定結果ファイル１０６ｈに格納された検定結果を、下記の比較分析処理にかけることにより、ＬＤブロックＩＤと、遺伝子シンボル名と、パーミュテーションを適用する際の試行回数と、パーミュテーションの結果、ある尤度以上の値が得られた回数と、尤度の算出に用いた統計量がカイ二乗分布に漸近的に従うとして計算したＰ値と、パーミュテーションによるＰ値と、ＳＮＰ総数と、ハプロタイプ総数と、対象とするＬＤブロックに含まれるＳＮＰ群の中でＳＮＰ検定部１０２ｆにて５％有意であったＳＮＰ数およびＳＮＰ総数と、ケース群の数と、コントロール群の数と、検定対象から除かれたサンプル数と、ケース群とコントロール群の合計数とを算出し、それぞれを比較分析結果ファイル１０６ｉの対応する項に格納する。
【０１４８】
ここで、比較分析部１０２ｇにおいて行われる比較分析処理の詳細を説明する。
【０１４９】
[比較分析処理]
ここでは、比較分析処理の詳細について図１７等を参照して説明する。図１７は、本実施形態における本システムの比較分析処理の一例を示すフローチャートである。なお、本実施形態は、有意ＳＮＰに着目してハプロタイプ解析結果と単点解析結果の比較を行う場合を一例に説明するが、本発明はかかる場合に限定されるものではなく、他の比較手法により実行してもよい。
【０１５０】
まず、ハプロタイプ解析装置１００は、有意ＳＮＰ抽出部１０２ｊの処理により、ステップＳＡ−７の処理によりＳＮＰ検定ファイル１０６ｈに格納された検定結果から有意であったＳＮＰを抽出する（ステップＳＤ−１）。
【０１５１】
ついで、ハプロタイプ解析装置１００は、有意ディプロタイプ抽出部１０２ｋの処理により、ステップＳＡ−５の処理により連鎖不平衡部位検定結果ファイル１０６ｇに格納された検定結果から有意であったディプロタイプを構成するＳＮＰを抽出する（ステップＳＤ−２）。
【０１５２】
さらに、ハプロタイプ解析装置１００は、一覧形式出力部１０２ｍの処理により、ステップＳＤ−１とステップＳＤ−２のそれぞれの抽出結果を一覧形式で出力装置１１４に出力し、当該抽出結果を比較分析結果ファイル１０６ｉの所定の領域に格納する（ステップＳＤ−３）。
これにて、比較分析処理が終了する。
【０１５３】
以上、メイン処理が終了する。
【０１５４】
[実施例]
次に、本発明の実施例について、図１８から図２６等を参照して詳細に説明する。なお、本実施例では、ＳＮＰタイピング結果と疾患データから疾患と関連する有意なＳＮＰパターン（ハプロタイプ）を推定する場合を一例に説明する。
【０１５５】
（本実施例の解析システムの流れ）
図１８は、本実施例における解析システムの流れの一例を示す図である。まず、生化学的実験よってサンプルのタイピングを行い、ＳＮＰサンプルデータを作成し、ＳＮＰデータベース（ＤＢ−２）の所定の領域に格納する（ステップＳＦ−１）。また、当該タイピングの過程において、サンプル情報や実験履歴や実験値などをＬＩＭＳデータベース（ＤＢ−１）の所定の領域に格納する。なお、ＳＮＰサンプルデータの示すタイピング結果とケースコントロール情報は、図２０を用いて後述する。
【０１５６】
ここで、本実施例のＳＮＰデータベース（ＤＢ−２）は、上述した実施形態のＳＮＰサンプルファイル１０６ａに対応する。
【０１５７】
ついで、ＳＮＰデータベース（ＤＢ−２）に格納されたＳＮＰサンプルデータをもとに、ハプロタイプ解析処理により、ハプロタイプと個人ごとのディプロタイプ型を推定し、ハプロタイプデータベース（ＤＢ−３）の所定の領域に格納する（ステップＳＦ−２）。
【０１５８】
ここで、本実施例のハプロタイプ解析処理（ステップＳＦ−２）は、上述した実施形態のディプロタイプ型決定部１０２ｂにて行われるディプロタイプ型決定処理に対応する。
【０１５９】
また、本実施例のハプロタイプデータベース（ＤＢ−３）は、上述した実施形態のハプロタイプＩＤ組ファイル１０６ｆに対応する。
【０１６０】
ついで、ハプロタイプデータベース（ＤＢ−３）の所定の領域に格納されたハプロタイプデータと、予め医療情報データベース（ＤＢ−４）に格納されている、ＳＮＰサンプルデータをケース群とコントロール群に分類するための分類情報を基に、疾患関連解析処理を行い（ステップＳＦ−３）、当該疾患関連解析処理の結果に対しレポート生成処理を行い、レポートを作成する（ステップＳＦ−４）。
【０１６１】
ここで、本実施例の疾患関連解析処理（ステップＳＦ−３）は、上述した実施形態の連鎖不平衡部位検定部１０２ｅ、または、ＳＮＰ検定部１０２ｆにて行われる遺伝的異質性検定処理に対応する。また、本実施例のレポート生成処理（ステップＳＦ−４）は、上述した実施形態の比較分析部１０２ｇにて行われる比較分析処理に対応する。
【０１６２】
（ハプロタイプ解析と単点解析の同時大量実行）
図１９は、本実施例におけるハプロタイプ解析と単点解析を同時に大量実行するための一例を示すフローチャートである。まず、単点解析において、上述した実施形態のケースコントロール情報ファイル１０６ｃに格納されている医療情報等のサンプル情報をもとにＳＮＰサンプルデータをカットオフ値によりケース群とコントロール群に分け、上述した実施形態のケースコントロール分類結果ファイル１０６ｂの所定の領域に格納する（ステップＳＥ−１−１）。また、ハプロタイプ解析においても、単点解析同様に行う（ステップＳＥ−１−２）。
【０１６３】
ここで、本実施例のケース群とコントロール群の分割の処理（ステップＳＥ−１−１、ステップＳＥ−１−２）は、上述した実施形態の分割部１０２ｄにて行われる処理に対応する。
【０１６４】
ついで、単点解析において、単点解析用ＤＡＴファイル群を生成し、上述した実施形態のハプロタイプＩＤ組ファイル１０６ｆの所定の領域に格納する（ステップＳＥ−２−１）。また、ハプロタイプ解析においても、ハプロタイプ解析用ＤＡＴファイル群を生成する（ステップＳＥ−２−２）。
【０１６５】
ここで、本実施例のＤＡＴファイル群生成処理（ステップＳＥ−２−１、ステップＳＥ−２−２）は、上述した実施形態のハプロタイプＩＤ組記憶部１０２ｃにて行われる処理に対応する。
【０１６６】
ついで、生成されたＤＡＴファイル群を入力セットとしてＦＰＭＰプログラムの処理を実行して単点解析レポートを作成し、当該単点解析レポートを上述した実施形態のＳＮＰ検定結果ファイル１０６ｈの所定の領域に格納する（ステップＳＥ−３）。
【０１６７】
なお、ハプロタイプ解析においても、ステップＳＥ−３と同様の処理を行い、作成されたハプロタイプ解析レポートを上述した実施形態の連鎖不平衡部位検定結果ファイル１０６ｇの所定の領域に格納する。
【０１６８】
ここで、本実施例のＦＰＭＰプログラムの処理（ステップＳＥ−３）は、上述した実施形態の連鎖不平衡部位検定部１０２ｅ、または、ＳＮＰ検定部１０２ｆにて行われる遺伝的異質性検定処理に対応する。
【０１６９】
さらに、ステップＳＥ−３の処理により得られた単点解析レポート、ハプロタイプ解析レポートを比較し、比較分析レポートを作成する（ステップＳＥ−４）。
【０１７０】
ここで、本実施例の比較分析レポート作成処理（ステップＳＥ−４）は、上述した実施形態の比較分析部１０２ｇにて行われる比較分析処理に対応する。
【０１７１】
（タイピング結果とケースコントロール情報）
図２０は、本実施例におけるタイピング結果とケースコントロール情報の一例を示す図である。なお、本実施例のタイピング結果とケースコントロール情報は、上述した実施形態のケースコントロール情報ファイル１０６ｃの所定の領域に格納されている情報に対応する。
【０１７２】
本図に示すように、タイピング結果とケースコントロール情報は、例えば、各サンプルを一意に識別するためのサンプルＩＤの表示領域ＭＡ−１と、疾患指標の表示領域（疾患指標１表示領域ＭＡ−２と、疾患指標２表示領域ＭＡ−３）と、ＳＮＰタイピング結果の表示領域ＭＡ−４とを含んで構成されている。
【０１７３】
ここで、本図において、例えば、各個人に対してサンプルＩＤが割り当てられており、ケース（患者）とコントロール（健常者）とを分けるのに２種類の指標（疾患指標１、疾患指標２）が使われている。
【０１７４】
ここで、疾患指標１はＰ（Ｐｏｓｉｔｉｖｅ）、Ｎ（Ｎｅｇａｔｉｖｅ）の２値である。また、疾患指標２は連続値のデータで、適切なカットオフ値を設定することでケースとコントロールを分けることが出来る。また、「Ｔ」で始まる番号はＳＮＰを表し、各個人ごとにＳＮＰのタイプ（ＡＡ、ＡＢ、ＢＢ）などが割り当てられている。また、「××」はＳＮＰタイピングで測定不能だった欠損データを表す。
【０１７５】
具体的には、例えば、サンプルＩＤが「０００１３９８０１」のものは、疾患指標１が「Ｐ」、疾患指標２が「３４」であり、ＳＮＰタイピング結果は、「Ｔ００４４１８」のＳＮＰタイプが「ＡＢ」、「Ｔ００４４２０」のＳＮＰタイプが「ＡＢ」、「Ｔ００４４２７」のＳＮＰタイプが「ＢＢ」、「Ｔ００４４２８」のＳＮＰタイプが「ＡＡ」、「Ｔ００４４３５」のＳＮＰタイプが「ＡＢ」、「Ｔ００４４３６」のＳＮＰタイプが「ＢＢ」、「Ｔ００４４３８」のＳＮＰタイプが「ＡＡ」、「Ｔ００４４４５」のＳＮＰタイプが「ＢＢ」、「Ｔ００４４４６」のＳＮＰタイプが「ＡＢ」であることが示されている。
【０１７６】
なお、ＳＮＰサンプルデータをどのようにしてケース群とコントロール群に分けるかは、対象とする疾患や医療情報によって異なるが、例えば、ある医学的根拠のある医療指標に着目し、医学的根拠のあるカットオフ値との比較により、ケース群「１」、コントロール群「０」に分けてもよい。
【０１７７】
（ディプロタイプ型の推定結果）
図２１は、本実施例における個人のディプロタイプ型の推定結果の一例を示す図である。なお、本実施例の個人のディプロタイプ型の推定結果は、上述した実施形態のディプロタイプ型決定部１０２ｂの処理により出力され、上述した実施形態のディプロタイプ型管理ファイル１０６ｅの所定の領域に格納される。
【０１７８】
本図に示すように、ディプロタイプ型の推定結果は、例えば、各サンプルを一意に識別するためのサンプル番号の表示領域ＭＢ−１と、ディプロタイプ番号の表示領域ＭＢ−２と、ディプロタイプ型を構成する各ハプロタイプの表示領域ＭＢ−３と、ディプロタイプ型の予想確率の表示領域ＭＢ−４を含んで構成されている。
【０１７９】
ここで、本図において、例えば、サンプル番号が２３番の個人には２種類のディプロタイプ型が予想されており、「ＢＡＢＡＢ−ＡＡＡＡＡ」型が９９．９％の確率、「ＢＡＢＡＡ−ＡＡＡＡＢ」型が０．１％の確率であると推定されていることが示されている。
【０１８０】
なお、これまで、本発明者等の実験では、ＳＮＰサンプルデータにノイズが少なければ、ほとんど１００％に近い確率で個人のディプロタイプ型が予想できることが確かめられている。
【０１８１】
（ハプロタイプＩＤ付与）
図２２は、本実施例におけるハプロタイプＩＤ付与の一例を示す図である。なお、本実施例のハプロタイプＩＤ付与の結果は、上述した実施形態のハプロタイプＩＤ組記憶部１０２ｃの処理により出力され、上述した実施形態のＬＤブロック管理ファイル１０６ｄの所定の領域に格納される。
【０１８２】
本図に示すように、ハプロタイプＩＤ付与は、例えば、各ＬＤブロックを一意に識別するためのＬＤブロックＩＤの表示領域ＭＣ−１と、各ＬＤブロックのハプロタイプを一意に識別するためのハプロタイプＩＤの表示領域ＭＣ−２と、各ハプロタイプのハプロタイプ頻度の表示領域ＭＣ−３と、各ＬＤブロックに属するハプロタイプ頻度から得られる頻度順位の表示領域ＭＣ−４と、各ハプロタイプの配列の表示領域ＭＣ−５を含んで構成されている。
【０１８３】
ここで、本図において、例えば、ＬＤブロックＩＤが、「６９」番のＬＤブロックには、４種類のハプロタイプがあり、ハプロタイプＩＤが「１」番が最も高頻度で全体の６１．７％を占めており、その配列は「ＢＢＢＡ」であることが示されている。
【０１８４】
なお、本実施例においては、ハプロタイプの頻度順位に基づいてハプロタイプのＩＤを決めているが、本発明はかかる場合に限定されるものではなく、他のＩＤの付与手法を用いてもよい。
【０１８５】
さて、ＳＮＰタイピングの結果により個人の遺伝子型は決定するが、一般にそれらがどのハプロタイプの組み合わせからなるのかは一意には決定しない。例えば、個人の遺伝子型が「ＢＢ」、「ＢＢ」、「ＡＢ」、「ＡＢ」だとすると、ハプロタイプの組み合わせは、「ＢＢＡＡ」、「ＢＢＢＢ」の可能性と、「ＢＢＡＢ」、「ＢＢＢＡ」の可能性があり、どちらが正しいかは決定出来ない。
【０１８６】
しかし、ＳＮＰサンプルのハプロタイプ頻度情報を分析することにより「ＢＢＡＡ」や「ＢＢＢＢ」のハプロタイプが見出される頻度が極めて少なく、「ＢＢＡＢ」と「ＢＢＢＡ」が高頻度で現れることがわかるので、「ＢＢＡＢ」と「ＢＢＢＡ」の組み合わせが妥当であると確率的に推論することが可能である。
【０１８７】
そして、各ハプロタイプには一意にＩＤが付与されているので、「ＢＢＢＡ」（ハプロタイプＩＤ＝１）、「ＢＢＡＢ」（ハプロタイプＩＤ＝２）の組み合わせは、「１−２」という様に表現することが出来る。
【０１８８】
なお、仮に、あるＬＤブロックに含まれるＳＮＰ数をＮとすると、可能なハプロタイプ数は２のＮ乗、可能なディプロタイプ数は（２のＮ乗）×（２のＮ乗）となるが、実際にはＮが大きくなれば、ハプロタイプ数は数個（Ｍ個）に収束し、可能なディプロタイプ数はＭの２乗となる。
【０１８９】
ここで、Ｎはパラメータとして任意に設定可能だが、本発明者等の実験から、本発明の疾患関連解析にはＮは５以下が適切であると考えられる。
【０１９０】
（ディプロタイプ番号の決定結果）
図２３は、本実施例におけるディプロタイプ番号の決定結果の一例を示す図である。なお、本実施例のディプロタイプ番号の決定結果は、上述した実施形態のハプロタイプＩＤ組記憶部１０２ｃの処理により出力され、上述した実施形態のハプロタイプＩＤ組ファイル１０６ｆの所定の領域に格納される。
【０１９１】
本図に示すように、ディプロタイプ番号の決定結果は、各サンプルを一意に識別するためのサンプルＩＤの表示領域ＭＤ−１と、ディプロタイプ型を一意に識別するためのディプロタイプ番号（ハプロタイプ番号の組）の表示領域ＭＤ−２とを含んで構成されている。
【０１９２】
ここで、本図において、例えば、サンプルＩＤが「０００１３Ｃ８５Ａ」の個人のディプロタイプ番号（ハプロタイプＩＤ組）は「２−３」であることが示されている。
【０１９３】
なお、本実施例においては、個人のディプロタイプ型を一意に決定するにあたり、図２１における予想確率が「８０％以上」であるディプロタイプ型を、また、図２２におけるハプロタイプＩＤ付与手法を採用条件とする。
【０１９４】
もし、当該採用条件を満たしたディプロタイプが複数存在した場合は、この数値の大きい方を採用する。また、当該採用条件を満たすディプロタイプが存在しなかった場合は、ディプロタイプ型が不確定であったことを示す特別なマーカー（例えば、「０」）などを個人のディプロタイプ型に対応付ける。ただし、本発明はかかる場合に限定されるものではなく、他の採用条件を用いてもよい。
【０１９５】
ここで、本図のように、「個人のサンプルＩＤ」、「ハプロタイプ１番号」、「ハプロタイプ２番号」の３つからなるファイルを「ＤＡＴ形式ファイル」と呼ぶ。ＤＡＴ形式ファイルは、本実施例のハプロタイプ解析以外に、シングルマーカーの単点ＳＮＰ解析においても「個人のサンプルＩＤ」、「アレル１番号」、「アレル２番号」として全く同様の形式でＦＰＭＰプログラムの入力セットとすることが出来る。
【０１９６】
（ＦＰＭＰによるパーミュテーション検定結果）
図２４は、本実施例におけるＦＰＭＰプログラムによるパーミュテーション検定の結果の一例を示す図である。なお、本実施例のＦＰＭＰプログラムによるパーミュテーション検定の結果は、上述した実施形態の連鎖不平衡部位検定部１０２ｅ、または、ＳＮＰ検定部１０２ｆの処理により出力される。
【０１９７】
本図に示すように、パーミュテーション検定の結果は、例えば、最尤法により得られた尤度と、自由度と、これに対応するカイ二乗分布のＰ値の表示領域ＭＥ−１と、乱数発生のためのシーズとなる数と、パーミュテーション法を適用する際の試行回数の表示領域ＭＥ−２と、表示領域ＭＥ−２に表示されている試行回数分のパーミュテーションを試行した結果、尤度が表示領域ＭＥ−１に表示されている尤度以上になった回数の表示領域ＭＥ−３と、Ｔ５検定におけるパーミュテーション法によるＰ値（ｅｍｐｉｒｉｃａｌ Ｐ）の表示領域ＭＥ−４とを含んで構成されている。
【０１９８】
ここで、本図は、ＭＥ−１に示す情報により、最尤法により得られた尤度が「１２．２８」、自由度が「８」、これに対応するカイ二乗分布のＰ値が「０．１３９１」であることが示されている。
【０１９９】
つづいて、ＭＥ−２に示す情報により、乱数発生のためのシーズとなる数が「３０００」、パーミュテーション法を適用する際の試行回数が「２００００」であることが示されている。
【０２００】
つづいて、ＭＥ−３に示す情報により、２００００回のパーミュテーションを試行した結果、尤度が１２．２８以上になった回数が「６７０３」であることが示されている。
【０２０１】
さらに、ＭＥ−４に示す情報により、Ｔ５検定におけるパーミュテーション法によるＰ値（ｅｍｐｉｒｉｃａｌ Ｐ）が「０．３３５２」であることが示されている。
【０２０２】
（ＦＰＭＰプログラムによる大量解析の結果）
図２５は、本実施例におけるＦＰＭＰプログラムによる大量解析の結果の一例を示す図である。なお、本実施例のＦＰＭＰプログラムによる大量解析の結果は、上述した実施形態の連鎖不平衡部位検定部１０２ｅ（ＳＮＰ検定部１０２ｆ）の処理により出力され、上述した実施形態の連鎖不平衡部位検定結果ファイル１０６ｇ（ＳＮＰ検定結果ファイル１０６ｈ）の所定の領域に格納される。
【０２０３】
本図に示すように、ＦＰＭＰプログラムによる大量解析の結果は、例えば、ＬＤブロックを一意に識別するためのＬＤブロックＩＤ（ｆｉｌｅｎａｍｅ）の表示領域ＭＦ−１と、尤度（ＭＬ）の表示領域ＭＦ−２と、カイ二乗分布の自由度（ｄｆ）の表示領域ＭＦ−３と、尤度の算出に用いた統計量がカイ二乗分布に漸近的に従うとして計算したＰ値（ａｓｙＰ：ａｓｙｍｐｔｏｔｉｃ Ｐ）の表示領域ＭＦ−４と、パーミュテーション法を適用する際の試行回数（Ｎｕｍ）の表示領域ＭＦ−５と、パーミュテーション法の結果、表示領域ＭＦ−２の尤度以上の値が得られた回数（Ｒｅａｃｈ）の表示領域ＭＦ−６と、パーミュテーション法によるＰ値（ｅｍｐＰ：ｅｍｐｉｒｉｃａｌ Ｐ）の表示領域ＭＦ−７と、ケース群の数（ｃａｓｅ）の表示領域ＭＦ−８と、コントロール群の数（ｃｏｎｔｒｏｌ）の表示領域ＭＦ−９と、ディプロタイプ型が一意に決定しなかった等の理由から検定対象から除かれたサンプルの数（ｍｉｓｓｉｎｇ）の表示領域ＭＦ−１０と、ケース群とコントロール群の合計数（ｃａｓｅ＋ｃｏｎｔｒｏｌ）の表示領域ＭＦ−１１とを含んで構成されている。
【０２０４】
ここで、例えば、本図において最初のデータであるＬＤブロックＩＤが「ＹＡ−００３．ＣＣ３７６−１０１４０２．ＦＥＨＰ＿ＯＵＴ．ＡＢＣＡ１．Ｔ００００３４．Ｔ００２６２６」において、尤度が「１２．２８」、自由度が「８」、尤度算出に用いた統計量がカイ二乗分布に漸近的に従うとして計算したＰ値（ａｓｙｍｐｔｏｔｉｃ Ｐ（ａｓｙＰ））が「０．１３９１」であることが示されている。
【０２０５】
つづいて、パーミュテーション法を適用する際の試行回数が「２００００」、パーミュテーションの結果により尤度値１２．２８以上の値が得られた回数が「６７０３」、パーミュテーション法によるＰ値（ｅｍｐＰ：ｅｍｐｉｒｉｃａｌＰ）が「０．３３５２」であることが示されている。
【０２０６】
さらに、ケース数（ｃａｓｅ）が「１４１」、コントロール数（ｃｏｎｔｒｏｌ）が「２１９」、ディプロタイプ型が一意に決まらなかった、または、検定対象として不適当であったため検定対象から除かれたサンプル数（ｍｉｓｓｉｎｇ）が「１６」、検定対象となったケースとコントロールの合計数（ｃａｓｅ＋ｃｏｎｔｒｏｌ）が「３６０」であることが示されている。
【０２０７】
（単点ＳＮＰ解析の結果とハプロタイプ解析の結果の照合）
図２６は、本実施例における単点ＳＮＰ解析とハプロタイプ解析の結果を一覧形式で出力した一例を示す図である。なお、当該単点ＳＮＰ解析とハプロタイプ解析の結果は、上述した実施形態の比較分析部１０２ｇの一覧形式出力部１０２ｍの処理により出力され、上述した実施形態の比較分析結果ファイル１０６ｉの所定の領域に格納される。
【０２０８】
本図に示すように、単点ＳＮＰ解析とハプロタイプ解析の結果は、例えば、ＬＤブロックを一意に識別するためのＬＤブロックＩＤの表示領域ＭＧ−１と、ＬＤブロックが属する遺伝子のシンボル名の表示領域ＭＧ−２と、パーミュテーション法を適用する際の試行回数の表示領域ＭＧ−３と、パーミュテーション法の結果ある尤度以上の値が得られた回数（Ｒｅａｃｈ）の表示領域ＭＧ−４と、尤度の算出に用いた統計量がカイ二乗分布に漸近的に従うとして計算したＰ値（ａｓｙＰ：ａｓｙｍｐｔｏｔｉｃ Ｐ）の表示領域ＭＧ−５と、パーミュテーション法によるＰ値（ｅｍｐＰ：ｅｍｐｉｒｉｃａｌ Ｐ）の表示領域ＭＧ−６と、ＳＮＰ総数の表示領域ＭＧ−７と、ハプロタイプ総数の表示領域ＭＧ−８と、対象とするＬＤブロックに含まれるＳＮＰ群の中で単点解析にて５％有意であったＳＮＰ数（有意ＳＮＰ数）およびＳＮＰ総数の表示領域ＭＧ−９と、対象とするＬＤブロックに含まれるＳＮＰ群のリスト（ＳＮＰリスト）の表示領域ＭＧ−１０と、ケース群の数（ｃａｓｅ）の表示領域ＭＧ−１１と、コントロール群の数（ｃｏｎｔｒｏｌ）の表示領域ＭＧ−１２と、ディプロタイプ型が一意に決定しなかった等の理由から検定対象から除かれたサンプルの数（ｍｉｓｓｉｎｇ）の表示領域ＭＧ−１３と、ケース群とコントロール群の合計数（ｃａｓｅ＋ｃｏｎｔｒｏｌ）の表示領域ＭＧ−１４とを含んで構成されている。
【０２０９】
なお、ＳＮＰリストの表示領域ＭＧ−１０において、単点解析にて５％有意であったＳＮＰに「＊」の印を付している。
【０２１０】
ここで、例えば、本図において最初のデータであるＬＤブロックＩＤが「ＹＡ−００３．ＣＣ３７６−１０１４０２．ＡＰ１Ｇ１．Ｔ００２２２３．Ｔ００２４２８」において、当該ＬＤブロックが属する遺伝子名が「＊＊」、パーミュテーション法を適用する際の試行回数が「２２００００」、パーミュテーションの結果によりある尤度値以上の値が得られた回数が「０」であることが示されている。
【０２１１】
つづいて、尤度算出に用いた統計量がカイ二乗分布に漸近的に従うとして計算したＰ値（ａｓｙＰ：ａｓｙｍｐｔｏｔｉｃ Ｐ）が「０」、パーミュテーション法によるＰ値（ｅｍｐＰ：ｅｍｐｉｒｉｃａｌ Ｐ）が「０」、当該ＬＤブロックに含まれるＳＮＰ数（＃ｓｎｐ）が「３」、当該ＬＤブロックのハプロタイプ数（＃ｈａｐｌｏｔｙｐｅ）が「４」であることが示されている。
【０２１２】
つづいて、当該ＬＤブロックに含まれるＳＮＰ群の中で単点ＳＮＰ解析にて５％有意だったＳＮＰ数（＃ｐｏｓｉｔｉｖｅ｜＃ｈａｐ）が「３つのＳＮＰのうち１つ（１｜３）」、当該ＬＤブロックに含まれるＳＮＰのリスト（ＳＮＰｌｉｓｔｓ）が「Ｔ００２２２３、Ｔ００２４２９、Ｔ００２４２８」であることが示されている。
【０２１３】
さらに、ケース数（ｃａｓｅ）が「１４８」、コントロール数（ｃｏｎｔｒｏｌ）が「２２７」、ディプロタイプ型が一意に決まらなかったなどの理由のため検定対象とならなかったサンプル数が「１」、検定対象となったケースとコントロールの合計数（ｃａｓｅ＋ｃｏｎｔｒｏｌ）が「３７５」であることが示されている。
【０２１４】
なお、ＳＮＰリストの表示領域ＭＧ−１０における「Ｔ００２４２９」に付されている「＊」は、単点解析にて５％有意であったことを示している。
【０２１５】
[他の実施の形態]
さて、これまで本発明の実施の形態について説明したが、本発明は、上述した実施の形態以外にも、上記特許請求の範囲に記載した技術的思想の範囲内において種々の異なる実施の形態にて実施されてよいものである。
【０２１６】
例えば、ハプロタイプ解析装置１００がスタンドアローンの形態で処理を行う場合を一例に説明したが、ハプロタイプ解析装置１００とは別筐体で構成されるクライアント端末からの要求に応じて処理を行い、その処理結果を当該クライアント端末に返却するように構成してもよい。
【０２１７】
また、実施形態において説明した各処理のうち、自動的に行なわれるものとして説明した処理の全部または一部を手動的に行うこともでき、あるいは、手動的に行なわれるものとして説明した処理の全部または一部を公知の方法で自動的に行うこともできる。
【０２１８】
この他、上記文書中や図面中で示した処理手順、制御手順、具体的名称、各種の登録データや検索条件等のパラメータを含む情報、画面例、データベース構成については、特記する場合を除いて任意に変更することができる。
【０２１９】
また、ハプロタイプ解析装置１００に関して、図示の各構成要素は機能概念的なものであり、必ずしも物理的に図示の如く構成されていることを要しない。
例えば、ハプロタイプ解析装置１００の各部または各装置が備える処理機能、特に制御部１０２にて行なわれる各処理機能については、その全部または任意の一部を、ＣＰＵ（Ｃｅｎｔｒａｌ Ｐｒｏｃｅｓｓｉｎｇ Ｕｎｉｔ）および当該ＣＰＵにて解釈実行されるプログラムにて実現することができ、あるいは、ワイヤードロジックによるハードウェアとして実現することも可能である。なお、プログラムは、後述する記録媒体に記録されており、必要に応じてハプロタイプ解析装置１００に機械的に読み取られる。
【０２２０】
すなわち、ＲＯＭまたはＨＤなどの記憶部１０６などには、ＯＳ（Ｏｐｅｒａｔｉｎｇ Ｓｙｓｔｅｍ）と協働してＣＰＵに命令を与え、各種処理を行うためのコンピュータプログラムが記録されている。このコンピュータプログラムは、ＲＡＭ等にロードされることによって実行され、ＣＰＵと協働して制御部１０２を構成する。また、このコンピュータプログラムは、ハプロタイプ解析装置１００に対して任意のネットワーク３００を介して接続されたアプリケーションプログラムサーバに記録されてもよく、必要に応じてその全部または一部をダウンロードすることも可能である。
【０２２１】
また、本発明にかかるプログラムを、コンピュータ読み取り可能な記録媒体に格納することもできる。ここで、この「記録媒体」とは、フレキシブルディスク、光磁気ディスク、ＲＯＭ、ＥＰＲＯＭ、ＥＥＰＲＯＭ、ＣＤ−ＲＯＭ、ＭＯ、ＤＶＤ等の任意の「可搬用の物理媒体」や、各種コンピュータシステムに内蔵されるＲＯＭ、ＲＡＭ、ＨＤ等の任意の「固定用の物理媒体」、あるいは、ＬＡＮ、ＷＡＮ、インターネットに代表されるネットワークを介してプログラムを送信する場合の通信回線や搬送波のように、短期にプログラムを保持する「通信媒体」を含むものとする。
【０２２２】
また、「プログラム」とは、任意の言語や記述方法にて記述されたデータ処理方法であり、ソースコードやバイナリコード等の形式を問わない。なお、「プログラム」は必ずしも単一的に構成されるものに限られず、複数のモジュールやライブラリとして分散構成されるものや、ＯＳ（Ｏｐｅｒａｔｉｎｇ Ｓｙｓｔｅｍ）に代表される別個のプログラムと協働してその機能を達成するものをも含む。なお、実施の形態に示した各装置において記録媒体を読み取るための具体的な構成、読み取り手順、あるいは、読み取り後のインストール手順等については、周知の構成や手順を用いることができる。
【０２２３】
記憶部１０６に格納される各種のファイル等（ＳＮＰサンプルファイル１０６ａ〜比較分析結果ファイル１０６ｉ）は、ＲＡＭ、ＲＯＭ等のメモリ装置、ハードディスク等の固定ディスク装置、フレキシブルディスク、光ディスク等のストレージ手段であり、各種処理やウェブサイト提供に用いる各種のプログラムやテーブルやファイルやデータベースやウェブページ用ファイル等を格納する。
【０２２４】
また、ハプロタイプ解析装置１００は、既知のパーソナルコンピュータ、ワークステーション等の情報処理端末等の情報処理装置にプリンタやモニタやイメージスキャナ等の周辺装置を接続し、該情報処理装置に本発明の方法を実現させるソフトウェア（プログラム、データ等を含む）を実装することにより実現してもよい。
【０２２５】
さらに、ハプロタイプ解析装置１００の分散・統合の具体的形態は図示のものに限られず、その全部または一部を、各種の負荷等に応じた任意の単位で、機能的または物理的に分散・統合して構成することができる。例えば、各データベースを独立したデータベース装置として独立に構成してもよく、また、処理の一部をＣＧＩ（Ｃｏｍｍｏｎ Ｇａｔｅｗａｙ Ｉｎｔｅｒｆａｃｅ）を用いて実現してもよい。
【０２２６】
また、ネットワーク３００は、ハプロタイプ解析装置１００と外部システム２００とを相互に接続する機能を有し、例えば、インターネットや、イントラネットや、ＬＡＮ（有線／無線の双方を含む）や、ＶＡＮや、パソコン通信網や、公衆電話網（アナログ／デジタルの双方を含む）や、専用回線網（アナログ／デジタルの双方を含む）や、ＣＡＴＶ網や、ＩＭＴ２０００方式、ＧＳＭ方式またはＰＤＣ／ＰＤＣ―Ｐ方式等の携帯回線交換網／携帯パケット交換網や、無線呼出網や、Ｂｌｕｅｔｏｏｔｈ等の局所無線網や、ＰＨＳ網や、ＣＳ、ＢＳまたはＩＳＤＢ等の衛星通信網等のうちいずれかを含んでもよい。すなわち、本システムは、有線・無線を問わず任意のネットワークを介して、各種データを送受信することができる。
【０２２７】
【発明の効果】
以上詳細に説明したように、本発明によれば、ＳＮＰサンプルデータから連鎖不平衡部位を抽出し、抽出された連鎖不平衡部位についてディプロタイプ型を決定し、決定されたディプロタイプ型についてハプロタイプＩＤの組を対応付けて記憶し、ＳＮＰサンプルデータを特定の指標情報に基づいてケース群とコントロール群に分割し、すべての連鎖不平衡部位に対して、分割されたケース群とコントロール群のそれぞれに対応するディプロタイプ型のハプロタイプＩＤの組を複数座位の遺伝子型を表現した多値の単一マーカーとみなして遺伝的異質性の検定を行い、すべてのＳＮＰに対して、分割されたケース群とコントロール群のアレル型を表す２値の単一マーカーについて遺伝的異質性の検定を行い、両検定結果を比較分析するので、検定の自由度が少なくなり検定結果の精度を高めることができるハプロタイプ解析装置、および、ハプロタイプ解析方法をコンピュータに実行させることを特徴とするプログラムを提供することができる。
【０２２８】
また、本発明によれば、ケース群とコントロール群をあわせてハプロタイプ頻度を予想するので、サンプルサイズが大きい分、正確な予想ができるハプロタイプ解析装置、および、ハプロタイプ解析方法をコンピュータに実行させることを特徴とするプログラムを提供することができる。
【０２２９】
また、本発明によれば、単点解析とハプロタイプ解析双方に対して、共通の入力形式で遺伝的異質性の検定を適用することができるので、大量解析に用いることができるハプロタイプ解析装置、および、ハプロタイプ解析方法をコンピュータに実行させることを特徴とするプログラムを提供することができる。
【０２３０】
また、本発明によれば、検定の精度を上げるために低頻度のハプロタイプ（マイナーハプロタイプ）を足切りすることがないので、マイナーハプロタイプが重要な役割を果たしている疾患を見逃す危険をさけることができるハプロタイプ解析装置、および、ハプロタイプ解析方法をコンピュータに実行させることを特徴とするプログラムを提供することができる。
【０２３１】
また、本発明によれば、連鎖不平衡部位についてディプロタイプ型の事後確率を推定し、推定された事後確率と予め定めた閾値とを比較し、比較結果に従って連鎖不平衡部位についてディプロタイプ型を決定するので、個人のディプロタイプ型をほぼ一意に決定することができるハプロタイプ解析装置、および、ハプロタイプ解析方法をコンピュータに実行させることを特徴とするプログラムを提供することができる。
【０２３２】
また、本発明によれば、２×ｍの分割表に対して最尤度比を用いたパーミュテーション検定を用いるので、検定表が疎（ｓｐａｒｓｅ：０を多く含む）でハプロタイプ数が多くなった場合においてもカイ二乗近似を正確におこなうことができるハプロタイプ解析装置、および、ハプロタイプ解析方法をコンピュータに実行させることを特徴とするプログラムを提供することができる。
【０２３３】
さらに、本発明によれば、ＳＮＰ検定による検定結果により有意であったＳＮＰを抽出し、連鎖不平衡部位検定による検定結果により有意であったディプロタイプを構成するＳＮＰを抽出し、両抽出結果を一覧形式で出力するので、単点解析とハプロタイプ解析の結果を相互比較することによって、ハプロタイプの中のどのＳＮＰが単点で有意であったか、ＳＮＰの組み合わせがどのような疾患にどのような影響をもたらしているかを推測することができるハプロタイプ解析装置、および、ハプロタイプ解析方法をコンピュータに実行させることを特徴とするプログラムを提供することができる。
【図面の簡単な説明】
【図１】本発明の基本原理を示すフローチャートである。
【図２】本発明が適用される本システムの構成の一例を示すブロック図である。
【図３】本発明が適用される本システムのディプロタイプ型決定部１０２ｂの構成の一例を示すブロック図である。
【図４】本発明が適用される本システムの比較分析部１０２ｇの構成の一例を示すブロック図である。
【図５】ＳＮＰサンプルファイル１０６ａに格納される情報の一例を示す図である。
【図６】ケースコントロール分類結果ファイル１０６ｂに格納される情報の一例を示す図である。
【図７】ケースコントロール情報ファイル１０６ｃに格納される情報の一例を示す図である。
【図８】ＬＤブロック管理ファイル１０６ｄに格納される情報の一例を示す図である。
【図９】ディプロタイプ型管理ファイル１０６ｅに格納される情報の一例を示す図である。
【図１０】ハプロタイプＩＤ組ファイル１０６ｆに格納される情報の一例を示す図である。
【図１１】連鎖不平衡部位検定結果ファイル１０６ｇに格納される情報の一例を示す図である。
【図１２】ＳＮＰ検定結果ファイル１０６ｈに格納される情報の一例を示す図である。
【図１３】比較分析結果ファイル１０６ｉに格納される情報の一例を示す図である。
【図１４】本実施形態における本システムのメイン処理の一例を示すフローチャートである。
【図１５】本実施形態における本システムのディプロタイプ型決定処理の一例を示すフローチャートである。
【図１６】本実施形態における本システムの遺伝的異質性検定処理の一例を示すフローチャートである。
【図１７】本実施形態における本システムの比較分析処理の一例を示すフローチャートである。
【図１８】本実施例における解析システムの流れの一例を示す図である。
【図１９】本実施例におけるハプロタイプ解析と単点解析を同時に大量実行するための一例を示すフローチャートである。
【図２０】本実施例におけるタイピング結果とケースコントロール情報の一例を示す図である。
【図２１】本実施例における個人のディプロタイプ型の推定結果の一例を示す図である。
【図２２】本実施例におけるハプロタイプＩＤの付与の一例を示す図である。
【図２３】本実施例におけるディプロタイプ番号の決定結果の一例を示す図である。
【図２４】本実施例におけるＦＰＭＰプログラムによるパーミュテーション検定の結果の一例を示す図である。
【図２５】本実施例におけるＦＰＭＰプログラムによる大量解析の結果の一例を示す図である。
【図２６】本実施例における単点ＳＮＰ解析とハプロタイプ解析の結果を一覧形式で出力した一例を示す図である。
【符号の説明】
１００ ハプロタイプ解析装置
１０２ 制御部
１０２ａ 連鎖不平衡部位抽出部
１０２ｂ ディプロタイプ型決定部
１０２ｃ ハプロタイプＩＤ組記憶部
１０２ｄ 分割部
１０２ｅ 連鎖不平衡部位検定部
１０２ｆ ＳＮＰ検定部
１０２ｇ 比較分析部
１０２ｈ 事後確率推定部
１０２ｉ 事後確率比較部
１０２ｊ 有意ＳＮＰ抽出部
１０２ｋ 有意ディプロタイプ抽出部
１０２ｍ 一覧形式出力部
１０４ 通信制御インターフェース部
１０６ 記憶部
１０６ａ ＳＮＰサンプルファイル
１０６ｂ ケースコントロール分類結果ファイル
１０６ｃ ケースコントロール情報ファイル
１０６ｄ ＬＤブロック管理ファイル
１０６ｅ ディプロタイプ型管理ファイル
１０６ｆ ハプロタイプＩＤ組ファイル
１０６ｇ 連鎖不平衡部位検定結果ファイル
１０６ｈ ＳＮＰ検定結果ファイル
１０６ｉ 比較分析結果ファイル
１０８ 入出力制御インターフェース部
１１２ 入力装置
１１４ 出力装置
２００ 外部システム
３００ ネットワーク[0001]
BACKGROUND OF THE INVENTION
The present invention relates to a program characterized by causing a computer to execute a haplotype analysis apparatus and a haplotype analysis method, and in particular, from a large amount of case control information related to SNPs, a haplotype that is significantly related to a disease is highly accurately detected. The present invention relates to a haplotype analyzer that can be extracted at high speed, and a program that causes a computer to execute a haplotype analysis method.
[0002]
[Prior art]
In recent years, the outlines of the base sequences of about 3 billion human genomes have been elucidated, comprehensively examining what traits the gene sequences relate to, and their knowledge for prevention, diagnosis and treatment There are growing expectations for research aimed at the realization of so-called custom-made medicine, which is going to be useful in the future. Differences in constitutions such as high blood pressure and diabetes are considered to be related to many genetic individual differences, and SNP (snip: single nucleotide polymorphism) is an important measure of individual differences in genes. It is considered as an index (for example, see Non-Patent Document 1).
[0003]
In order to realize customized medicine, it is necessary to link specific SNPs and specific clinical data, but in general diseases, there are estimated to be more than 10 genes related to each other, and each gene has several dozens. Since SNPs are included, it is very difficult to determine which combination is clinically meaningful from a vast number of combinations and requires technical ingenuity (for example, non-patent literature) 2). One key is to statistically narrow down combinations of SNPs called haplotypes by grouping genetically related SNPs (in linkage disequilibrium), and the other key is from possible haplotypes To extract clinically meaningful haplotypes.
[0004]
With regard to the former, in recent years, various software for calculating haplotype frequencies from a plurality of genotype data of a plurality of loci linked to each other has been developed. Many of them use the EM algorithm to estimate the haplotype frequency of a population from genotype data by the maximum likelihood method (see, for example, Non-Patent Document 1 and Non-Patent Document 3).
[0005]
Regarding the latter, a case control study is generally applied to test whether there is a significant difference in genetic index such as SNP frequency between healthy subjects and patients. In this method, a group having a disease and a group having no disease are separately collected, and a difference in genetic properties of the group is tested for a significant difference. A method of analyzing a significant difference between a case and a control using one SNP as a marker is called a single point analysis, and a method of analyzing a significant difference using a plurality of SNPs as a marker is called a multipoint analysis. The chi-square test using a 2 × 2 contingency table is usually used for a significant difference test. However, a 2 × m contingency table is also a Markov that increases the reliability of the test and enables an independence test. A chained Monte Carlo method, a permutation method, and the like have also been proposed (see, for example, Non-Patent Document 1, Non-Patent Document 4, and Non-Patent Document 5).
[0006]
[Non-Patent Document 1]
Naoya Kamaya, “Genetic Statistics in the Post-Genomic Era”, Yochisha, 2001
[Non-Patent Document 2]
Masaaki Muramatsu, “Utilizing individual differences in genes for medical treatment”, Nikkei Science, Nikkei Inc., January 2002, p. 28-35
[Non-Patent Document 3]
Schneider S. Et al., “Arlequin: A software for population genetic data analysis”, Ver. 1.1, Genetics and Biometry Lab. , Dept. of Anthropology, Univ. Geneva, 1997
[Non-Patent Document 4]
Jing Hua Zhao, David Curtis, Pak Chung Sham, “Model-Free Analysis and Permutation Tests for Allic Association”, Hum Hered 2000, 50, p. 133-139
[Non-Patent Document 5]
Manabu Iwasaki, “Statistical Analysis of Incomplete Data”, Economist, 2002
[Non-Patent Document 6]
Hiroto Matsumine, “Science of the Brain”, Seiwa Shoten, 1998, 20, p. 281
[0007]
[Problems to be solved by the invention]
However, as described above, in order to determine which SNP combination among the enormous combinations is clinically meaningful, 1) to determine the haplotype with high accuracy in real time, and 2) to be predicted It is necessary to identify haplotypes involved in the disease from the haplotype group.
[0008]
Regarding 1), as described above, various software has been developed, but when analyzing large-scale data, for example, 10,000 SNPs with 100 people, it actually exists from the theoretical haplotype of 2 to the 10,000th power. A haplotype is selected, and real-time processing is difficult if existing software is used as it is. In addition, in order to identify a haplotype related to a disease, a technical device for constructing a haplotype suitable for a disease-related analysis method is required.
[0009]
As described above, 2) can be examined by examining whether there is a significant difference in the frequency of haplotypes between a healthy person and a patient by a case control study. Usually, chi-square test or the like is used for the test of significant difference, but this test method is inaccurate in chi-square approximation when the test table is sparse (including many: sparse: 0) and the number of haplotypes increases. There is a problem of becoming.
[0010]
In general, in the haplotype frequency difference test between the target disease group and the healthy subject group, a sparse 2 × m (m: number of haplotypes) test table consisting of a large number of haplotypes will be handled. Ingenuity is required.
[0011]
In the conventional method, the haplotype frequency estimation for N people in the disease group and the haplotype frequency estimation for the healthy group M people are performed separately to compare whether there is a significant difference in frequency distribution between the two. Has the following problems.
[0012]
First, there is a high possibility that haplotypes estimated in the disease group and haplotypes estimated in the healthy group are not common, and there is a problem that the frequency distribution cannot be compared for them.
[0013]
Further, since the sample size N of the disease group and the sample size M of the healthy subject group are smaller than the entire sample size (N + M), there is a problem that the reliability of estimation of the haplotype is lowered.
[0014]
In addition, in order to improve the accuracy of the test, haplotypes (minor haplotypes) that are less frequent are cut off, but there is a problem that the minor haplotypes may play an important role depending on the disease (for example, (Refer nonpatent literature 6 mentioned above.).
[0015]
Furthermore, there is a problem that the calculation cost is increased by separately performing the haplotype estimation of the disease group and the healthy group.
[0016]
As described above, the conventional system or the like has a number of problems, and as a result, it is inconvenient and inefficient for both the system user and the administrator.
[0017]
The present invention was made in view of the above problems, and from a large amount of case control information related to SNPs, a haplotype analyzer that can extract a haplotype significant in relation to a disease with high accuracy and high speed, and An object of the present invention is to provide a program characterized by causing a computer to execute a haplotype analysis method.
[0018]
[Means for Solving the Problems]
To achieve these goals, The present invention The haplotype analyzer of the present invention includes a linkage disequilibrium site extraction means for extracting linkage disequilibrium sites from SNP sample data, and a diplotype for determining a diplotype type for the linkage disequilibrium sites extracted by the linkage disequilibrium site extraction means. Based on specific index information, type type determining means, haplotype ID set storage means for storing a set of haplotype IDs in association with the diplotype type determined by the diplotype type determining means, and the SNP sample data Dividing means for dividing into a case group and a control group, and the diplotype haplotype corresponding to each of the case group and the control group divided by the dividing means for all the linkage disequilibrium sites Multi-valued single marker that expresses genotypes of multiple loci for ID pairs A linkage disequilibrium site test means for performing genetic heterogeneity tests, and a binary single representing allele types of the case group and the control group divided by the division means for all the SNPs. Characterized in that it comprises SNP test means for testing genetic heterogeneity for the marker, and comparison analysis means for comparing and analyzing the test result by the linkage disequilibrium site test means and the test result by the SNP test means. To do.
[0019]
According to this apparatus, a linkage disequilibrium site is extracted from SNP sample data, a diplotype type is determined for the extracted linkage disequilibrium portion, and a set of haplotype IDs is stored in association with the determined diplotype type. The SNP sample data is divided into a case group and a control group based on specific index information, and the diplotype haplotype ID corresponding to each of the divided case group and control group is divided for all linkage disequilibrium sites. 2 is represented as a multi-value single marker expressing multiple loci genotypes, and genetic heterogeneity tests are performed, and all SNPs represent allele types of divided case groups and control groups. Since the test of genetic heterogeneity is performed for a single marker of values and the results of both tests are compared and analyzed, the degree of freedom of the test is reduced. It is possible to increase the constant results accuracy.
[0020]
In addition, since the haplotype frequency is predicted by combining the case group and the control group, the larger the sample size, the more accurate prediction can be made.
[0021]
Moreover, since the low frequency haplotype (minor haplotype) is not cut off in order to improve the accuracy of the test, the risk of missing a disease in which the minor haplotype plays an important role can be avoided.
[0022]
Also, The present invention The haplotype analyzer of the above In the haplotype analyzing apparatus described above, the diplotype type determining means includes the posterior probability estimating means for estimating the diplotype posterior probability for the linkage disequilibrium site, and the above-mentioned thing estimated by the posterior probability estimating means. A posterior probability comparing means for comparing the posterior probability with a predetermined threshold is further provided, wherein the diplotype type is determined for the linkage disequilibrium site according to the comparison result by the posterior probability comparing means.
[0023]
This more specifically shows one example of the diplotype type determining means. According to this apparatus, the posterior probability of the diplotype type is estimated for the linkage disequilibrium portion, the estimated posterior probability is compared with a predetermined threshold value, and the diplotype type is determined for the linkage disequilibrium portion according to the comparison result. Therefore, the individual diplotype type can be almost uniquely determined by the posterior probability of the diplotype type.
[0024]
Also, The present invention The haplotype analyzer of the above In the described haplotype analyzer, the genetic heterogeneity test is characterized by using a permutation test using a maximum likelihood ratio for a 2 × m contingency table.
[0025]
This is a more specific example of a genetic heterogeneity test. According to this apparatus, since the permutation test using the maximum likelihood ratio is used for the 2 × m contingency table, when the test table is sparse (including many: 0) and the number of haplotypes increases. The chi-square approximation can also be accurately performed in.
[0026]
In addition, since the genetic heterogeneity test can be applied to both single-point analysis and haplotype analysis by using the same test method, high-throughput mass analysis can be performed simultaneously.
[0027]
Also, The present invention The haplotype analyzer of the above In the haplotype analyzer described above, the comparative analysis means is significant by the significant SNP extraction means for extracting SNPs that are significant from the test results by the SNP test means and the test results by the linkage disequilibrium site test means. A significant diplotype extracting means for extracting SNPs constituting the diplotype; and a list format outputting means for outputting the extraction result by the significant SNP extracting means and the extraction result by the significant diplotype extracting means in a list format. It is characterized by that.
[0028]
This more specifically shows one example of comparative analysis means. According to this apparatus, SNPs that are significant as a result of the test by the SNP test are extracted, SNPs that constitute a diplotype that is significant as a result of the test by the linkage disequilibrium site test are extracted, and both extraction results are listed. Therefore, by comparing the results of single-point analysis and haplotype analysis with each other, which SNPs in the haplotype were significant at a single point, and what effect the combination of SNPs has on what diseases You can guess what it is.
[0029]
In addition, combining single-point analysis results and haplotype analysis results can provide more effective and deeper insights for tailor-made diagnosis and drug discovery targets.
[0030]
The present invention also relates to a program, The present invention The program includes a linkage disequilibrium site extraction step for extracting a linkage disequilibrium site from SNP sample data, and a diplotype type for determining a diplotype type for the linkage disequilibrium site extracted in the linkage disequilibrium site extraction step. A determination step, a haplotype ID set storage step for storing a haplotype ID set in association with the diplotype type determined in the diplotype type determination step, and a case where the SNP sample data is based on specific index information A division step that divides into a group and a control group, and the haplotype ID of the diplotype corresponding to each of the case group and the control group divided by the division step for all the linkage disequilibrium sites. The group expressed the genotype of multiple loci Linkage disequilibrium site test step in which genetic heterogeneity test is performed assuming that the value is a single marker, and for all the SNPs, the allele types of the case group and the control group divided by the division step are A SNP test step for testing genetic heterogeneity for the binary marker represented, a comparison analysis step for comparing and analyzing the test result by the linkage disequilibrium site test step and the test result by the SNP test step. A haplotype analysis method is executed by a computer.
[0031]
According to this program, a linkage disequilibrium site is extracted from SNP sample data, a diplotype type is determined for the extracted linkage disequilibrium site, and a set of haplotype IDs is stored in association with the determined diplotype type. The SNP sample data is divided into a case group and a control group based on specific index information, and the diplotype haplotype ID corresponding to each of the divided case group and control group is divided for all linkage disequilibrium sites. 2 is represented as a multi-value single marker expressing multiple loci genotypes, and genetic heterogeneity tests are performed, and all SNPs represent allele types of divided case groups and control groups. Since the test of genetic heterogeneity is performed for a single marker of values and the results of both tests are compared and analyzed, the degree of freedom of the test is small. It is possible to improve the accuracy of the assay results.
[0032]
In addition, since the haplotype frequency is predicted by combining the case group and the control group, the larger the sample size, the more accurate prediction can be made.
[0033]
Moreover, since the low frequency haplotype (minor haplotype) is not cut off in order to improve the accuracy of the test, the risk of missing a disease in which the minor haplotype plays an important role can be avoided.
[0034]
Also, The present invention The program of the above In the program described above, the diplotype determination step includes a posterior probability estimation step for estimating the diplotype posterior probability for the linkage disequilibrium site, and the posterior probability estimated in the posterior probability estimation step. And a posterior probability comparison step for comparing the threshold value with a predetermined threshold, and determining the diplotype type for the linkage disequilibrium site according to the comparison result of the posterior probability comparison step.
[0035]
This shows one example of the diplotype type determination step more specifically. According to this program, the posterior probability of the diplotype type is estimated for the linkage disequilibrium portion, the estimated posterior probability is compared with a predetermined threshold value, and the diplotype type is determined for the linkage disequilibrium portion according to the comparison result. Therefore, the individual diplotype type can be almost uniquely determined by the posterior probability of the diplotype type.
[0036]
Also, The present invention The program of the above In the described program, the genetic heterogeneity test is characterized by using a permutation test using a maximum likelihood ratio for a 2 × m contingency table.
[0037]
This is a more specific example of a genetic heterogeneity test. According to this program, since the permutation test using the maximum likelihood ratio is used for the 2 × m contingency table, the test table is sparse (including many: zero) and the number of haplotypes increases. The chi-square approximation can also be accurately performed in.
[0038]
In addition, since the genetic heterogeneity test can be applied to both single-point analysis and haplotype analysis by using the same test method, high-throughput mass analysis can be performed simultaneously.
[0039]
Also, The present invention The program of the above In the program described above, the comparative analysis step includes a significant SNP extraction step for extracting a SNP that is significant based on the test result in the SNP test step, and a diplopro that is significant based on the test result in the linkage disequilibrium site test step. A significant diplotype extraction step for extracting SNPs constituting the type, and a list format output step for outputting the extraction result of the significant SNP extraction step and the extraction result of the significant diplotype extraction step in a list format. Features.
[0040]
This more specifically shows an example of the comparative analysis step. According to this program, SNPs that are significant as a result of the test by the SNP test are extracted, SNPs that constitute a diplotype that is significant as a result of the test by the linkage disequilibrium site test are extracted, and both extraction results are displayed in a list format. Therefore, by comparing the results of single-point analysis and haplotype analysis with each other, which SNPs in the haplotype were significant at a single point, and what effect the combination of SNPs has on what diseases You can guess what it is.
[0041]
In addition, combining single-point analysis results and haplotype analysis results can provide more effective and deep insights for tailor-made diagnosis and drug discovery targets.
[0042]
The present invention also relates to a recording medium, and the recording medium of the present invention is Note The recorded program is recorded.
[0043]
According to this recording medium, by causing the computer to read and execute the program recorded on the recording medium, the above The described program can be realized using a computer, and the same effects as those of these methods can be obtained.
[0044]
DETAILED DESCRIPTION OF THE INVENTION
Embodiments of a program characterized by causing a computer to execute a haplotype analysis apparatus and a haplotype analysis method according to the present invention will be described below in detail with reference to the drawings. Note that the present invention is not limited to the embodiments.
[0045]
[Outline of the present invention]
Hereinafter, the outline of the present invention will be described, and then the configuration and processing of the present invention will be described in detail. FIG. 1 is a flowchart showing the basic principle of the present invention.
[0046]
The present invention generally has the following basic features. That is, the present invention first extracts linkage disequilibrium sites from the SNP sample data (step S-1).
[0047]
Next, the diplotype type is determined for the linkage disequilibrium site extracted in step S-1 (step S-2).
[0048]
Here, the diplotype type is determined by estimating the haplotype frequency and the individual diplotype distribution (the posterior probability of the individual diplotype type) with high accuracy from the genotype data of the population developed by the present inventors. A program named “LDSupport” may be employed.
[0049]
Next, the haplotype ID pair is stored in association with the diplotype type determined in step S-2 (step S-3).
[0050]
Here, as a method of associating a set of haplotype IDs in step S-3, for example, a method of assigning numbers in order from the highest haplotype frequency ranking may be used.
[0051]
Next, the SNP sample data is divided into a case (disease) group and a control (healthy person) group based on specific index information (step S-4).
[0052]
Here, how to divide the SNP sample data into the case group and the control group differs depending on the target disease and medical information, but for example, paying attention to a medical index with a certain medical basis, A method of classifying the case group as “1” and the control group as “0” by comparison with a certain cutoff value may be used.
[0053]
Next, for all linkage disequilibrium sites, a set of diplotype haplotype IDs corresponding to each of the case group and the control group divided in step S-4 is expressed as a multi-locus genotype. A genetic heterogeneity test is performed assuming that the value is a single marker (step S-5).
[0054]
Here, the genetic heterogeneity test in Step S-5 includes “FPMP (free-model analysis of for developing a permutation test using a 2 × m contingency table” developed by Zhao. permutation test using fast EH plus).
[0055]
Next, for all SNPs, genetic heterogeneity is tested for binary single markers representing allele types of the case group and the control group divided in step S-4 (step S-6). . Note that the genetic heterogeneity test method used in step S-6 is the same as the test method described in step S-5, and is therefore omitted.
[0056]
Further, the test result for the linkage disequilibrium site in step S-5 and the test result for the SNP in step S-6 are compared and analyzed (step S-7).
[0057]
Here, as a method of comparative analysis, for example, a method of analyzing how many SNPs among the SNPs of LD blocks that were significant were significant in the single SNP analysis, or not significant in the single SNP analysis For example, a technique of combining haplotypes by combining SNPs and analyzing significant SNPs may be used.
[0058]
[System configuration]
First, the configuration of this system will be described. FIG. 2 is a block diagram showing an example of the configuration of the system to which the present invention is applied, and conceptually shows only the portion related to the present invention in the configuration.
[0059]
This system schematically includes a haplotype analysis apparatus 100 that processes information related to SNP, disease information, and the like, and an external system 200 that provides an external database and various external programs related to SNP information and the like via a network 300. It is configured to be communicable.
[0060]
[System configuration: Haplotype analyzer 100]
Next, the configuration of the haplotype analysis apparatus 100 will be described. The haplotype analysis apparatus 100 is generally connected to a control unit 102 such as a CPU that controls the overall haplotype analysis apparatus 100 and a communication apparatus (not shown) such as a router connected to a communication line or the like. The communication control interface unit 104, the input / output control interface unit 108 connected to the input device 112 and the output device 114, and the storage unit 106 for storing various databases and files are configured. Are communicably connected via a communication path. Further, the haplotype analysis apparatus 100 is communicably connected to the network 300 via a communication device such as a router and a wired or wireless communication line such as a dedicated line.
[0061]
Various databases, tables, and files (SNP sample file 106a to comparative analysis result file 106i) stored in the storage unit 106 in FIG. 2 are storage means such as a fixed disk device, and various programs and tables used for various processes. And files, databases, web page files, etc.
[0062]
Among these components of the storage unit 106, the SNP sample file 106a is SNP sample data storage means for storing SNP sample data. Here, the SNP sample file 106a may be an external SNP database accessed via the Internet, or an in-house database created by copying these databases or storing original SNP information. But you can.
[0063]
FIG. 5 is a diagram illustrating an example of information stored in the SNP sample file 106a. The information stored in the SNP sample file 106a is configured by associating a sample ID for uniquely identifying each sample with a SNP ID for uniquely identifying the SNP, as shown in FIG. Yes.
[0064]
The case control classification result file 106b is a case control classification result storage unit that stores case control classification result information for each index of each sample. FIG. 6 is a diagram illustrating an example of information stored in the case control classification result file 106b.
[0065]
As shown in FIG. 6, the information stored in the case control classification result file 106b includes a sample ID for uniquely identifying each sample, and an index for uniquely identifying the case control classification result of each sample. Are related to each other.
[0066]
The case control information file 106c is a case control information storage unit that stores case control information (including disease information and SNP typing information) of each sample. FIG. 7 is a diagram illustrating an example of information stored in the case control information file 106c.
[0067]
As shown in FIG. 7, the information stored in the case control information file 106c includes a sample ID for uniquely identifying each sample, a disease index for uniquely identifying disease index information, and a unique SNP. SNPIDs for identifying each other are associated with each other.
[0068]
The LD block management file 106d is an LD block storage unit that stores information (including haplotype information, sequence information, and the like) related to LD blocks (linkage disequilibrium sites). FIG. 8 is a diagram showing an example of information stored in the LD block management file 106d.
[0069]
As shown in FIG. 8, the LD block management file 106d is obtained from an LD block ID for uniquely identifying each LD block, a haplotype ID for uniquely identifying a haplotype, a haplotype frequency, and a haplotype frequency. The frequency ranking and the sequence are correlated with each other.
[0070]
The diplotype type management file 106e is diplotype type information storage means for storing information about the diplotype type. FIG. 9 is a diagram showing an example of information stored in the diplotype management file 106e.
[0071]
As shown in FIG. 9, the diplotype type management file 106e includes a sample number for uniquely identifying each sample, a diplotype number, and an array of haplotype types that constitute the diplotype type (haplotype 1 sequence). And the haplotype 2 sequence) and the expected probability of the diplotype type.
[0072]
The haplotype ID set file 106f is haplotype ID set storage means for storing a diplotype number (a set of haplotype numbers) and the like. FIG. 10 is a diagram illustrating an example of information stored in the haplotype ID set file 106f.
[0073]
As shown in FIG. 10, the haplotype ID set file 106f is configured such that a sample ID for uniquely identifying each sample and a diplotype number (a set of haplotype numbers) for uniquely identifying a diplotype type are mutually associated. It is configured in association with.
[0074]
The linkage disequilibrium site test result file 106g is linkage disequilibrium site test result storage means for storing the linkage disequilibrium site test result. FIG. 11 is a diagram illustrating an example of information stored in the linkage disequilibrium site test result file 106g.
[0075]
As shown in FIG. 11, this linkage disequilibrium site test result file 106g is used to calculate the LD block ID, the likelihood, the degree of freedom of the chi-square distribution, and the likelihood for uniquely identifying the LD block. P value calculated asymptotically following the chi-square distribution (asyP: asymptotic P), the number of trials (Num) when applying the permutation method, and a certain likelihood as a result of the permutation method The number of times the above values were obtained (Reach), the P value by the permutation method (empP: empirical P), the number of cases (case), the number of controls (control), and the diplotype type The number of samples removed from the test subject due to reasons such as not being determined uniquely, and the total of the case group and the control group (Case + control) and that are correlated with each other.
[0076]
The SNP test result file 106h is SNP test result storage means for storing the SNP test result. FIG. 12 is a diagram illustrating an example of information stored in the SNP test result file 106h.
[0077]
As shown in FIG. 12, the SNP test result file 106h includes a SNP ID for uniquely identifying the SNP, a likelihood, a degree of freedom of the chi-square distribution, and a statistic used for calculating the likelihood. The P value calculated asymptotically following the distribution (asyP: asymptotic P), the number of trials when applying the permutation method (Num), and a value greater than a certain likelihood as a result of the permutation method were obtained. The number of times (Reach), the P value by the permutation method (empP: empirical P), the number of case groups (case), the number of control groups (control), the diplotype type was not uniquely determined, etc. The number of samples removed from the test subject for the reason (missing) and the total number of cases and control groups (case + cont) ol) and that are correlated with each other.
[0078]
The comparison analysis result file 106i is a comparison analysis result storage unit that stores a comparison analysis result. FIG. 13 is a diagram illustrating an example of information stored in the comparative analysis result file 106i.
[0079]
As shown in FIG. 13, the comparative analysis result file 106i includes an LD block ID for uniquely identifying an LD block, a symbol name of a gene to which the LD block belongs, and the number of trials when applying the permutation method. As a result of the permutation method, the number of times a value greater than a certain likelihood (Reach) and the P value calculated asymptotically following the chi-square distribution (asyP: asymptotic P), P value by the permutation method (empP: empirical P), total number of SNPs, total number of haplotypes, and 5% significant in single point analysis among SNP groups included in the target LD block The number of SNPs (number of significant SNPs) and the total number of SNPs, and a list of SNP groups included in the target LD block (SNP list ), The number of case groups (case), the number of control groups (control), the number of samples removed from the test subject (missing) because the diplotype type was not uniquely determined, etc. The total number of groups and control groups (case + control) is associated with each other.
[0080]
In FIG. 2, the communication control interface unit 104 performs communication control between the haplotype analysis apparatus 100 and the network 300 (or a communication apparatus such as a router). That is, the communication control interface unit 104 has a function of communicating data with other terminals via a communication line.
[0081]
In FIG. 2, the input / output control interface unit 108 controls the input device 112 and the output device 114. Here, as the output device 114, in addition to a monitor (including a home TV), a speaker can be used (hereinafter, the output device 114 may be described as a monitor). As the input device 112, a keyboard, a mouse, a microphone, or the like can be used. The monitor also realizes a pointing device function in cooperation with the mouse.
[0082]
In FIG. 2, the control unit 102 has a control program such as an OS (Operating System), a program defining various processing procedures, and an internal memory for storing necessary data. Information processing for executing various processes is performed. In terms of functional concept, the control unit 102 includes a linkage disequilibrium site extraction unit 102a, a diplotype type determination unit 102b, a haplotype ID set storage unit 102c, a division unit 102d, a linkage disequilibrium site test unit 102e, a SNP test unit 102f, and a comparison. An analysis unit 102g is included.
[0083]
Among these, the linkage disequilibrium part extraction part 102a is a linkage disequilibrium part extraction means which extracts a linkage disequilibrium part from SNP sample data.
[0084]
The diplotype type determining unit 102b is diplotype type determining means for determining a diplotype type for a linkage disequilibrium site. Here, the diplotype type determination unit 102b is configured to further include a posterior probability estimation unit 102h and a posterior probability comparison unit 102i, as shown in FIG.
[0085]
FIG. 3 is a block diagram showing an example of the configuration of the diplotype type determining unit 102b of the present system to which the present invention is applied, and conceptually shows only the portion related to the present invention.
[0086]
In FIG. 3, the posterior probability estimation unit 102h is posterior probability estimation means for estimating a diplotype posterior probability for a linkage disequilibrium site.
[0087]
The posterior probability comparison unit 102i is posterior probability comparison means for comparing the posterior probability with a predetermined threshold.
[0088]
Returning to FIG. 2 again, the haplotype ID set storage unit 102c is a haplotype ID set storage unit that stores a haplotype ID set in association with a diplotype type.
[0089]
The dividing unit 102d is a dividing unit that divides the SNP sample data into a case group and a control group based on specific index information.
[0090]
In addition, the linkage disequilibrium site test unit 102e is a multi-value representing a plurality of genotypes of diplotype haplotype IDs corresponding to each of the case group and the control group for all linkage disequilibrium sites. It is a linkage disequilibrium site test means for performing genetic heterogeneity test by considering the marker as a single marker.
[0091]
In addition, the SNP test unit 102f performs genetic heterogeneity tests on all SNP sample data with respect to binary single markers representing allele types of the case group and the control group divided by the division unit 102d. SNP test means.
[0092]
The comparative analysis unit 102g is a comparative analysis unit that performs comparative analysis of the linkage disequilibrium site test result and the SNP test result. Here, as shown in FIG. 4, the comparative analysis unit 102g further includes a significant SNP extraction unit 102j, a significant diplotype extraction unit 102k, and a list format output unit 102m.
[0093]
FIG. 4 is a block diagram showing an example of the configuration of the comparative analysis unit 102g of the system to which the present invention is applied, and conceptually shows only the portion related to the present invention in the configuration.
[0094]
In FIG. 4, a significant SNP extraction unit 102j is a significant SNP extraction unit that extracts SNPs that are significant based on the SNP test result.
[0095]
The significant diplotype extracting unit 102k is a significant diplotype extracting unit that extracts SNPs constituting diplotypes that are significant based on the linkage disequilibrium site test result.
[0096]
The list format output unit 102m is a list format output unit that outputs significant SNP extraction results and significant diplotype extraction results in a list format.
Details of processing performed by each of these units will be described later.
[0097]
[System configuration: external system 200]
Next, the configuration of the external system 200 will be described. The external system 200 is connected to the haplotype analysis apparatus 100 via the network 300, and has a function of providing a user with an external database regarding SNP information and the like and a website for executing various external programs.
[0098]
Here, the external system 200 may be configured as a WEB server, an ASP server, or the like, and the hardware configuration may be configured by an information processing apparatus such as a commercially available workstation or a personal computer and an accessory device thereof. Good. Each function of the external system 200 is realized by a CPU, a disk device, a memory device, an input device, an output device, a communication control device, and the like in the hardware configuration of the external system 200 and a program for controlling them.
[0099]
[System configuration: network 300]
Next, the configuration of the network 300 will be described. The network 300 has a function of connecting the haplotype analysis apparatus 100 and the external system 200 to each other, and is, for example, the Internet.
[0100]
[System processing]
Next, an example of the processing of the system according to the present embodiment configured as described above will be described in detail with reference to FIGS.
[0101]
[Main processing]
First, details of the main process will be described with reference to FIG. FIG. 14 is a flowchart showing an example of main processing of the system according to the present embodiment. In the present embodiment, the “LDSupport” program developed by the present inventors in the process of determining the diplotype type and the “FPMP” developed by Zhao in the process of the genetic heterogeneity test are described. The case where a program is used will be described as an example, but the present invention is not limited to such a case, and may be executed by another program.
[0102]
First, the haplotype analysis apparatus 100 extracts a linkage disequilibrium site (LD block) from SNP sample data to which a sample ID for identifying a sample is attached in advance by the processing of the linkage disequilibrium portion extraction unit 102a, and corresponds to the sample ID. And stored in the storage unit 106 (step SA-1).
[0103]
The SNP sample data is, for example, SNP sample data stored in advance in a predetermined area of the SNP sample file 106a, SNP sample data stored in advance in a predetermined area of the case control information file 106c, or an external system in advance. SNP sample data obtained by accessing 200 external databases and stored in a predetermined area of the SNP sample file 106a may be used.
[0104]
Next, the haplotype analysis apparatus 100 first assigns an LD block ID to each LD block for each of the LD blocks extracted in the process of step SA-1 by the process of the diplotype type determination unit 102b, and manages the LD block. It is stored in the “LD block ID” section of the file 106d. Next, for each of the LD blocks, a diplotype type determination process for uniquely determining the diplotype type of all individuals is executed, and information obtained by the diplotype type determination process (a diplotype type (a set of haplotype types) is determined. ), The prediction probability, the haplotype frequency, and the sequence corresponding to the haplotype frequency) are stored in predetermined areas of the LD block management file 106d and the diplotype management file 106e (step SA-2).
[0105]
Specifically, the diplotype type determination unit 102b stores the diplotype type (a haplotype type set) and the prediction probability in a predetermined storage area in the diplotype type management file 106e, and stores it in the LD block management file 106d. The haplotype frequency and the sequence corresponding to the haplotype frequency are stored in a predetermined storage area.
[0106]
Subsequently, the diplotype type determination unit 102b assigns numbers such as “1, 2, 3,...” In order from the haplotype type with the highest haplotype frequency, and the “frequency ranking” item of the LD block management file 106d. To store.
[0107]
Here, the diplotype type determination unit 102b assigns haplotype IDs such as “1, 2, 3,...” In order from the highest frequency ranking stored in the LD block management file 106d, and the haplotype ID. Is stored in the “haplotype ID” section of the LD block management file 106d.
[0108]
In the present embodiment, the above-described haplotype ID assignment method is employed. However, the present invention is not limited to this case, and other haplotype ID assignment methods may be employed.
[0109]
On the other hand, the diplotype type determination unit 102b assigns numbers such as “1, 2,...” According to the number of diplotype types stored in the diplotype type management file 106e, and the diplotype type management file It is stored in the “diplotype number” section of 106e.
[0110]
Further, the diplotype type determination unit 102b assigns a number so that it can be distinguished from other samples, and stores it in the “sample number” section of the diplotype type management file 106e.
[0111]
Here, the details of the diplotype type determination process performed in the diplotype type determination unit 102b will be described.
[0112]
[Diplotype determination process]
Here, the details of the diplotype type determination process will be described with reference to FIG.
FIG. 15 is a flowchart illustrating an example of the diplotype type determination process of the system according to the present embodiment. In the present embodiment, the case where the diplotype type is determined using a program named “LDSupport” developed by the present inventors will be described as an example. However, the present invention is not limited to such a case. It may be executed by another program.
[0113]
First, the haplotype analysis apparatus 100 constructs a diplotype type that each individual can take based on the LD block of the individual stored in the storage unit 106 by the process of step SA-1 by the process of the diplotype type determination unit 102b. Then, haplotype types that the group can take are identified (step SB-1).
[0114]
Next, the haplotype analysis apparatus 100 gives an initial value (non-zero value) of the haplotype frequency to each haplotype by the processing of the diplotype type determination unit 102b (step SB-2).
[0115]
Next, the haplotype analysis apparatus 100 calculates the diplotype likelihood for each individual by the processing of the posterior probability estimation unit 102h, assuming that the group is in Hardy-Weinberg equilibrium, and further uses Bayes' theorem. The posterior probability of each diplotype type is calculated (step SB-3).
[0116]
Next, the haplotype analysis apparatus 100 combines the likelihoods of the diplotype types for each individual calculated by the processing of step SB-3 for all the diplotypes by the processing of the diplotype type determination unit 102b, and further all the individuals. Are combined to calculate the likelihood as a group (step SB-4).
[0117]
Next, the haplotype analyzing apparatus 100 uses the posterior probability of each diplotype type for each individual calculated by the processing of step SB-3 by the processing of the diplotype type determination unit 102b, and the expected value of the number of haplotypes in the group. The haplotype frequency is updated by calculating (Step SB-5).
[0118]
Subsequently, the haplotype analysis apparatus 100 performs steps from step SB-1 until the likelihood as a group converges by using the haplotype frequency updated by the processing of step SB-5 by the processing of the diplotype type determination unit 102b. The process of SB-5 is repeated, and the haplotype frequency and the individual diplotype distribution (the posterior probability of the individual diplotype type) are estimated simultaneously (step SB-6).
[0119]
Furthermore, the haplotype analysis apparatus 100 sets a diplotype type that has a posterior probability of the individual diplotype type estimated by the process of step SB-6 to a threshold value or more as a personal diplotype type by the processing of the posterior probability comparison unit 102i. Adopt (step SB-7).
[0120]
Here, for example, first, a diplotype type having a threshold value (for example, 80%) or more is adopted as an individual diplotype type, and if there are a plurality of candidate diplotype types having a certain threshold value or more, the diplotype type is selected. Employ the larger posterior probability, and if there is no candidate diplotype, a special marker (for example, 0) indicating that the diplotype is indeterminate is assigned to the individual diplotype. You may employ | adopt the method of matching, etc.
This completes the diplotype type determination process.
[0121]
Returning to FIG. 14 again, the haplotype analysis apparatus 100 performs processing for each diplotype type in the diplotype type management file 106e in which information has already been stored by the processing of step SA-2 by the processing of the haplotype ID set storage unit 102c. A set of unique numbers is associated and stored in a predetermined area of the haplotype ID set file 106f (step SA-3).
[0122]
Specifically, the haplotype ID set storage unit 102c stores the set of unique numbers in the item “diplotype number (haplotype 1 number, haplotype 2 number)” of the haplotype ID set file 106f. Then, the haplotype ID set storage unit 102c copies the sample ID stored in the SNP sample file 106a or the case control information file 106c, and puts the diplotype in the “sample ID” section of the haplotype ID set file 106f. The sample ID is stored so as to correspond to the number.
[0123]
Here, the association of the unique number set may be associated with the unique number set, for example, based on the haplotype ID stored in the LD block management file 106d by the process of step SA-2. .
[0124]
Subsequently, the haplotype analysis apparatus 100 converts the SNP sample data into the case group and the control group based on the medical information data stored in the “disease index” section of the case control information file 106c in advance by the processing of the dividing unit 102d. The classification result is stored together with the corresponding sample ID in a predetermined area of the case control classification result file 106b (step SA-4).
[0125]
Here, the medical information data may be, for example, medical information data acquired by accessing an external database of the external system 200 and stored in the “disease index” section of the case control information file 106c.
[0126]
Further, how the SNP sample data stored in the case control information file 106c is divided into the case group and the control group differs depending on the target disease and medical information. A method of classifying the case group as “1” and the control group as “0” by comparing the cut-off value with a medical basis by paying attention to the index may be used.
[0127]
Next, the haplotype analysis apparatus 100 obtains a plurality of individual diplotype numbers (sets of haplotype type numbers) stored in the haplotype ID set file 106f determined in step SA-3 by the processing of the linkage disequilibrium site test unit 102e. A genetic heterogeneity test is performed together with the case control classification result stored in the case control classification result file 106b determined in step SA-4, assuming that it is a multi-value single marker expressing the genotype of the locus. The genetic heterogeneity test result is stored in a predetermined region of the linkage disequilibrium site test result file 106g (step SA-5).
[0128]
Specifically, the linkage disequilibrium site test unit 102e performs the following genetic heterogeneity test process so that the likelihood, the degree of freedom, and the statistic used to calculate the likelihood are asymptotic to the chi-square distribution. P value calculated as following, the number of trials when applying the permutation method, the number of times that a result of the permutation was greater than a certain likelihood, the P value by the permutation method, Link the number of case groups, the number of control groups, the number of samples excluded from the test because the diplotype type was not uniquely determined, and the total number of case groups and control groups. It stores in the corresponding term of the unbalanced part test result file 106g.
[0129]
Here, the details of the genetic heterogeneity test process performed in the linkage disequilibrium site test unit 102e will be described.
[0130]
[Genetic heterogeneity test]
Here, the details of the genetic heterogeneity test process will be described with reference to FIG. FIG. 16 is a flowchart showing an example of the genetic heterogeneity test process of the system according to the present embodiment. In the present embodiment, a case where a genetic heterogeneity test is performed on a linkage disequilibrium site using a program named “FPMP” developed by Zhao will be described. Can be used similarly. The present invention is not limited to such a case, and may be executed by another program.
[0131]
First, the haplotype analysis apparatus 100 randomly sorts the case control classification results of individual subjects stored in the case control classification result file 106b by the processing of the linkage disequilibrium site test unit 102e (step SC-1). .
[0132]
Specifically, the linkage disequilibrium site test unit 102e accesses the case control classification result file 106b, sorts the case control classification results randomly, and determines the number of case groups, the number of control groups, and the test. The number of samples to be excluded from the target and the sum of the case group and the control group are calculated, and each is stored in “case”, “control”, “missing”, “case + control” of the linkage disequilibrium site test result file 106g. .
[0133]
Next, the haplotype analysis apparatus 100 obtains the maximum likelihood ratio (LR (T5)) by the processing of the linkage disequilibrium site test unit 102e, and stores it in the “likelihood” section of the linkage disequilibrium site test result file 106g. (Step SC-2).
[0134]
Here, for example, the following formula 1 may be used as LR (T5).

[0135]
Note that the values of Lcase, Lcontrol, and Lcase + control in Equation 1 above are calculated by the linkage disequilibrium site test unit 102e based on the case control classification result stored in the case control classification result file 106b. It is the likelihood for the (patient) group, the control (healthy person) group, and the group of cases and controls.
[0136]
Returning to FIG. 16 again, the haplotype analysis apparatus 100 obtains the distribution under the null hypothesis of LR (T5) by the processing of the linkage disequilibrium site test unit 102e (step SC-3).
[0137]
Next, the haplotype analysis apparatus 100 predicts the haplotype frequency for each case, control, and case + control from the actual SNP sample data by the processing of the linkage disequilibrium site test unit 102e, and calculates LR (T5) (step SC). -4).
[0138]
Next, in the haplotype analysis apparatus 100, the LR (T5) obtained by the process of step SC-4 is sufficiently deviated from the distribution obtained by the process of step SC-3 by the process of the linkage disequilibrium site test unit 102e. After confirming this, the null hypothesis is rejected (step SC-5).
[0139]
Next, the haplotype analysis apparatus 100 performs the permutation test by repeating the processing from step SC-1 to step SC-5 for the designated number of times by the processing of the linkage disequilibrium site testing unit 102e (step SC-6). ).
[0140]
Specifically, the linkage disequilibrium site test unit 102e first stores the designated number in “Num” of the linkage disequilibrium site test result file 106g, executes a permutation test, and performs the permutation test. The number of times that a value greater than a certain likelihood is obtained as a result of the station test is stored in “Reach” of the linkage disequilibrium site test result file 106g.
[0141]
Further, the haplotype analysis apparatus 100 calculates the P value (empiricalP) based on the simulation of LR (T5) by the processing of the linkage disequilibrium site test unit 102e, and the term “empP” in the linkage disequilibrium site test result file 106g. (Step SC-7).
[0142]
This completes the genetic heterogeneity test process.
[0143]
Returning to FIG. 14 again, the haplotype analysis apparatus 100 applies the processing from step SA-2 to step SA-5 to all the LD blocks by the processing of the control unit 102 (step SA-6).
[0144]
Next, the haplotype analysis apparatus 100 performs a genetic heterogeneity test on all SNPs in the same manner as in step SA-5 by the processing of the SNP test unit 102f, and the results of the genetic heterogeneity test are SNPs. The data is stored in a predetermined area of the test result file 106h (step SA-7).
[0145]
Note that the genetic heterogeneity test performed by the SNP test unit 102f corresponds to the above-described genetic heterogeneity test process performed by the linkage disequilibrium site test unit 102e, and a description thereof will be omitted.
[0146]
Furthermore, the haplotype analysis apparatus 100 compares and analyzes the test result of step SA-5 and the test result of step SA-7 by the processing of the comparison analysis unit 102g, and the result of the comparison analysis is determined in a predetermined manner in the comparison analysis result file 106i. Store in the area (step SA-8).
[0147]
Specifically, the comparative analysis unit 102g applies the test results stored in the linkage disequilibrium site test result file 106g and the SNP test result file 106h to the following comparative analysis process, whereby the LD block ID, the gene symbol, Name, the number of trials when applying permutation, the number of times the permutation results in a value greater than a certain likelihood, and the statistics used to calculate the likelihood are asymptotic to the chi-square distribution SNP that was 5% significant in the SNP test unit 102f among the SNP group included in the target LD block, the P value calculated as per the following, the P value by permutation, the total number of SNPs, the total number of haplotypes Number and total number of SNPs, number of case groups, number of control groups, number of samples excluded from test subjects, total of case groups and control groups Calculating the door, they are stored respectively in the corresponding section of the comparative analysis results file 106i.
[0148]
Here, details of the comparative analysis processing performed in the comparative analysis unit 102g will be described.
[0149]
[Comparative analysis process]
Here, details of the comparative analysis processing will be described with reference to FIG. FIG. 17 is a flowchart showing an example of the comparative analysis process of the system according to the present embodiment. In addition, although this embodiment demonstrates as an example the case where a haplotype analysis result and a single point analysis result are compared paying attention to significant SNP, this invention is not limited to such a case, Other comparison methods May be executed.
[0150]
First, the haplotype analysis apparatus 100 extracts a significant SNP from the test result stored in the SNP test file 106h by the process of step SA-7 by the process of the significant SNP extraction unit 102j (step SD-1).
[0151]
Next, the haplotype analysis apparatus 100, by the processing of the significant diplotype extraction unit 102k, the SNP constituting the diplotype that is significant from the test result stored in the linkage disequilibrium site test result file 106g by the processing of step SA-5. Is extracted (step SD-2).
[0152]
Furthermore, the haplotype analysis apparatus 100 outputs the extraction results of step SD-1 and step SD-2 to the output device 114 in a list format by the processing of the list format output unit 102m, and the extraction results are compared with the comparison analysis result file. 106i is stored in a predetermined area (step SD-3).
This completes the comparative analysis process.
[0153]
Thus, the main process ends.
[0154]
[Example]
Next, embodiments of the present invention will be described in detail with reference to FIGS. In addition, a present Example demonstrates the case where the significant SNP pattern (haplotype) relevant to a disease is estimated from a SNP typing result and disease data as an example.
[0155]
(Flow of analysis system of this example)
FIG. 18 is a diagram illustrating an example of the flow of the analysis system in the present embodiment. First, a sample is typed by a biochemical experiment, SNP sample data is created, and stored in a predetermined area of the SNP database (DB-2) (step SF-1). In the typing process, sample information, experiment history, experiment values, and the like are stored in a predetermined area of the LIMS database (DB-1). The typing result and case control information indicated by the SNP sample data will be described later with reference to FIG.
[0156]
Here, the SNP database (DB-2) of the present example corresponds to the SNP sample file 106a of the above-described embodiment.
[0157]
Next, based on the SNP sample data stored in the SNP database (DB-2), the haplotype and the diplotype type for each individual are estimated by haplotype analysis processing, and the haplotype database (DB-3) is stored in a predetermined area. Store (step SF-2).
[0158]
Here, the haplotype analysis process (step SF-2) of the present example corresponds to the diplotype type determination process performed in the diplotype type determination unit 102b of the above-described embodiment.
[0159]
Further, the haplotype database (DB-3) of the present example corresponds to the haplotype ID set file 106f of the above-described embodiment.
[0160]
Next, haplotype data stored in a predetermined area of the haplotype database (DB-3) and SNP sample data stored in advance in the medical information database (DB-4) are classified into case groups and control groups. Based on the classification information, a disease-related analysis process is performed (step SF-3), a report generation process is performed on the result of the disease-related analysis process, and a report is created (step SF-4).
[0161]
Here, the disease-related analysis process (step SF-3) of the present example corresponds to the genetic heterogeneity test process performed in the linkage disequilibrium site test unit 102e or the SNP test unit 102f of the above-described embodiment. To do. Further, the report generation process (step SF-4) of the present example corresponds to the comparison analysis process performed by the comparison analysis unit 102g of the above-described embodiment.
[0162]
(Simultaneous mass execution of haplotype analysis and single point analysis)
FIG. 19 is a flowchart illustrating an example for simultaneously executing a large amount of haplotype analysis and single point analysis in the present embodiment. First, in the single point analysis, the SNP sample data is divided into the case group and the control group based on the cut-off value based on the sample information such as medical information stored in the case control information file 106c of the above-described embodiment. The data is stored in a predetermined area of the case control classification result file 106b of the embodiment (step SE-1-1). Also, the haplotype analysis is performed in the same manner as the single point analysis (step SE-1-2).
[0163]
Here, the process of dividing the case group and the control group (step SE-1-1 and step SE-1-2) of the present example corresponds to the process performed by the dividing unit 102d of the above-described embodiment.
[0164]
Next, in the single point analysis, a single point analysis DAT file group is generated and stored in a predetermined area of the haplotype ID set file 106f of the above-described embodiment (step SE-2-1). In the haplotype analysis, a DAT file group for haplotype analysis is generated (step SE-2-2).
[0165]
Here, the DAT file group generation processing (step SE-2-1 and step SE-2-2) of the present embodiment corresponds to the processing performed in the haplotype ID set storage unit 102c of the above-described embodiment.
[0166]
Next, the FPMP program processing is executed using the generated DAT file group as an input set to create a single point analysis report, and the single point analysis report is stored in a predetermined area of the SNP test result file 106h of the above-described embodiment. (Step SE-3).
[0167]
In the haplotype analysis, the same processing as step SE-3 is performed, and the created haplotype analysis report is stored in a predetermined area of the linkage disequilibrium site test result file 106g of the above-described embodiment.
[0168]
Here, the process of the FPMP program (step SE-3) of the present example corresponds to the genetic heterogeneity test process performed in the linkage disequilibrium site test unit 102e or the SNP test unit 102f of the above-described embodiment. To do.
[0169]
Further, the single point analysis report and the haplotype analysis report obtained by the processing in step SE-3 are compared to create a comparison analysis report (step SE-4).
[0170]
Here, the comparative analysis report creation process (step SE-4) of the present example corresponds to the comparative analysis process performed in the comparative analysis unit 102g of the above-described embodiment.
[0171]
(Typing results and case control information)
FIG. 20 is a diagram illustrating an example of typing results and case control information in the present embodiment. Note that the typing result and case control information in this example correspond to information stored in a predetermined area of the case control information file 106c in the above-described embodiment.
[0172]
As shown in the figure, the typing result and the case control information include, for example, a sample ID display area MA-1 for uniquely identifying each sample, and a disease index display area (disease index 1 display area MA-2). And a disease index 2 display area MA-3) and a SNP typing result display area MA-4.
[0173]
Here, in this figure, for example, a sample ID is assigned to each individual, and two types of indices (disease index 1, disease index 2) are used to separate a case (patient) and a control (healthy person). Is used.
[0174]
Here, the disease index 1 is a binary value of P (Positive) and N (Negative). The disease index 2 is continuous value data, and cases and controls can be separated by setting an appropriate cut-off value. A number starting with “T” represents an SNP, and an SNP type (AA, AB, BB) or the like is assigned to each individual. “XX” represents missing data that could not be measured by SNP typing.
[0175]
Specifically, for example, when the sample ID is “000139801”, the disease index 1 is “P” and the disease index 2 is “34”, and the SNP typing result is that the SNP type of “T004418” is “AB”. SNP type of “T004420” is “AB”, SNP type of “T004427” is “BB”, SNP type of “T004428” is “AA”, SNP type of “T004435” is “AB”, SNP type of “T004436” It is shown that the SNP type of “BB”, “T004438” is “AA”, the SNP type of “T004445” is “BB”, and the SNP type of “T004446” is “AB”.
[0176]
How to divide SNP sample data into case group and control group depends on the target disease and medical information, but for example, pay attention to a medical index with a medical basis, and there is a medical basis. You may divide into case group "1" and control group "0" by comparison with a cutoff value.
[0177]
(Diplotype type estimation result)
FIG. 21 is a diagram showing an example of the estimation result of the individual diplotype type in this embodiment. Note that the estimation result of the individual diplotype type in this embodiment is output by the processing of the diplotype type determination unit 102b of the above-described embodiment, and is stored in a predetermined area of the diplotype-type management file 106e of the above-described embodiment. Is done.
[0178]
As shown in the figure, the estimation result of the diplotype type includes, for example, a sample number display area MB-1 for uniquely identifying each sample, a diplotype number display area MB-2, and a diplotype type. The display area MB-3 of each haplotype and the display area MB-4 of the expected probability of the diplotype type are configured.
[0179]
Here, in this figure, for example, two types of diplotypes are expected for the individual whose sample number is No. 23, “BABAB-AAAAA” type is 99.9% probability, “BABAA-AAAAB” type Is estimated to have a probability of 0.1%.
[0180]
Until now, it has been confirmed by experiments by the present inventors that if the SNP sample data has little noise, an individual diplotype type can be predicted with a probability close to 100%.
[0181]
(Haplotype ID assignment)
FIG. 22 is a diagram illustrating an example of assigning a haplotype ID in the present embodiment. Note that the haplotype ID assignment result of this embodiment is output by the processing of the haplotype ID set storage unit 102c of the above-described embodiment, and is stored in a predetermined area of the LD block management file 106d of the above-described embodiment.
[0182]
As shown in the figure, the haplotype ID assignment is performed by, for example, an LD block ID display area MC-1 for uniquely identifying each LD block and a haplotype ID for uniquely identifying the haplotype of each LD block. Display region MC-2, haplotype frequency display region MC-3 of each haplotype, frequency ranking display region MC-4 obtained from haplotype frequencies belonging to each LD block, and display region MC-5 of each haplotype sequence It is comprised including.
[0183]
In this figure, for example, the LD block with the LD block ID “69” has four types of haplotypes, and the haplotype ID “1” has the highest frequency, accounting for 61.7% of the total. And the sequence is shown to be “BBBA”.
[0184]
In this embodiment, the haplotype ID is determined based on the frequency order of the haplotype. However, the present invention is not limited to this case, and other ID assigning methods may be used.
[0185]
Now, the genotype of an individual is determined by the result of SNP typing, but generally it does not uniquely determine which haplotype combination they comprise. For example, if an individual's genotype is “BB”, “BB”, “AB”, “AB”, the haplotype combination can be “BBAA”, “BBBB”, and “BBAB”, “BBBA”. There is a nature, and it cannot be decided which is right.
[0186]
However, by analyzing the haplotype frequency information of the SNP sample, it is found that the frequency of “BBAA” and “BBBB” haplotypes is extremely low, and that “BBAB” and “BBBA” appear frequently, so that “BBAB” And “BBBA” can be reasonably inferred that the combination is valid.
[0187]
Since each haplotype has a unique ID, the combination of “BBBA” (haplotype ID = 1) and “BBAB” (haplotype ID = 2) should be expressed as “1-2”. I can do it.
[0188]
If the number of SNPs included in a certain LD block is N, the number of possible haplotypes is 2 to the Nth power and the number of possible diplotypes is (2 to the Nth power) × (2 to the Nth power). Actually, when N increases, the number of haplotypes converges to several (M), and the number of possible diplotypes becomes the square of M.
[0189]
Here, N can be arbitrarily set as a parameter, but from experiments by the present inventors, it is considered that N is suitably 5 or less for the disease-related analysis of the present invention.
[0190]
(Diplotype number determination result)
FIG. 23 is a diagram illustrating an example of the determination result of the diplotype number in the present embodiment. The determination result of the diplotype number in this embodiment is output by the processing of the haplotype ID set storage unit 102c of the above-described embodiment, and is stored in a predetermined area of the haplotype ID set file 106f of the above-described embodiment.
[0191]
As shown in the figure, the determination result of the diplotype number includes a sample ID display area MD-1 for uniquely identifying each sample, and a diplotype number (haplotype number for uniquely identifying the diplotype type). Display area MD-2.
[0192]
In this figure, for example, the diplotype number (haplotype ID set) of the individual whose sample ID is “00013C85A” is “2-3”.
[0193]
In this embodiment, in order to uniquely determine an individual's diplotype type, the diplotype type having an expected probability of “80% or more” in FIG. 21 and the haplotype ID assignment method in FIG. 22 are used. And
[0194]
If there are multiple diplotypes that satisfy the employment conditions, the larger one is adopted. Further, when there is no diplotype that satisfies the employment condition, a special marker (for example, “0”) indicating that the diplotype type is indefinite is associated with the individual diplotype type. However, the present invention is not limited to such a case, and other employment conditions may be used.
[0195]
Here, as shown in the figure, a file consisting of “personal sample ID”, “haplotype 1 number”, and “haplotype 2 number” is called a “DAT format file”. In addition to the haplotype analysis of this embodiment, the DAT format file is also used in the FPMP program in the same format as “individual sample ID”, “allele 1 number”, and “allele 2 number” in single-point single-point SNP analysis. It can be an input set.
[0196]
(Permutation test result by FPMP)
FIG. 24 is a diagram illustrating an example of a result of permutation test by the FPMP program in the present embodiment. Note that the result of the permutation test by the FPMP program of the present example is output by the processing of the linkage disequilibrium site test unit 102e or the SNP test unit 102f of the above-described embodiment.
[0197]
As shown in the figure, the result of the permutation test is, for example, the likelihood obtained by the maximum likelihood method, the degree of freedom, and the corresponding P-value display area ME-1 of the chi-square distribution, Number of seeds for random number generation, number of trials when applying permutation method display area ME-2, and permutation for the number of trials displayed in display area ME-2 As a result, the display area ME-3 whose number of times the likelihood is equal to or greater than the likelihood displayed in the display area ME-1, and the display area ME-4 of the P value (empirical P) by the permutation method in the T5 test It is comprised including.
[0198]
Here, according to the information shown in ME-1, the likelihood obtained by the maximum likelihood method is “12.28”, the degree of freedom is “8”, and the corresponding P value of the chi-square distribution is “8”. 0.1391 ".
[0199]
Subsequently, the information shown in ME-2 indicates that the number of seeds for generating random numbers is “3000” and the number of trials when applying the permutation method is “20000”.
[0200]
Subsequently, the information shown in ME-3 indicates that the number of times that the likelihood has reached 12.28 or more as a result of trying 20000 permutations is “6703”.
[0201]
Furthermore, the information shown in ME-4 indicates that the P value (empirical P) by the permutation method in the T5 test is “0.3352”.
[0202]
(Results of mass analysis using FPMP program)
FIG. 25 is a diagram illustrating an example of a result of mass analysis by the FPMP program in the present embodiment. In addition, the result of the mass analysis by the FPMP program of this example is output by the processing of the linkage disequilibrium site test unit 102e (SNP test unit 102f) of the above-described embodiment, and the linkage disequilibrium site test result of the above-described embodiment. It is stored in a predetermined area of the file 106g (SNP test result file 106h).
[0203]
As shown in this figure, the result of the mass analysis by the FPMP program is, for example, an LD block ID (filename) display area MF-1 for uniquely identifying an LD block, and a likelihood (ML) display area MF. -2, the display area MF-3 of the degree of freedom (df) of the chi-square distribution, and the P value (asyP: asymptotic P) calculated that the statistic used for calculating the likelihood asymptotically follows the chi-square distribution As a result of the display area MF-4, the display area MF-5 of the number of trials (Num) when applying the permutation method, and the permutation method, a value greater than the likelihood of the display area MF-2 is obtained. Display area MF-6 for the number of times (Reach), display area MF-7 for the P value (empP: empirical P) by the permutation method, and the number of cases (case) Display area MF-8, display area MF-9 for the number of control groups (control), and display of the number of samples removed from the test object (missing) because the diplotype type was not uniquely determined An area MF-10 and a display area MF-11 for the total number of cases and controls (case + control) are configured.
[0204]
Here, for example, when the LD block ID which is the first data in this figure is “YA-003.CC376-101402.FEHP_OUT.ABCA1.T000034.T002626”, the likelihood is “12.28” and the degree of freedom is “8”. It is shown that the P value (asymptotic P (asyP)) calculated assuming that the statistic used for likelihood calculation asymptotically follows the chi-square distribution is “0.1391”.
[0205]
Subsequently, the number of trials when applying the permutation method is “20000”, the number of times the likelihood value of 12.28 or more is obtained as a result of the permutation is “6703”, and the permutation method P It is shown that the value (empP: empiricalP) is “0.3352”.
[0206]
Furthermore, the number of cases removed from the test subject because the case number (141), the control number (control) is “219”, and the diplotype type was not uniquely determined or was inappropriate as the subject of the test. (Missing) is “16”, and the total number of cases and controls (case + control) to be tested is “360”.
[0207]
(Verification of single-point SNP analysis results and haplotype analysis results)
FIG. 26 is a diagram illustrating an example in which the results of single-point SNP analysis and haplotype analysis in this embodiment are output in a list format. The results of the single-point SNP analysis and haplotype analysis are output by the processing of the list format output unit 102m of the comparison analysis unit 102g of the above-described embodiment, and are stored in a predetermined region of the comparison analysis result file 106i of the above-described embodiment. Stored.
[0208]
As shown in this figure, the results of single-point SNP analysis and haplotype analysis are, for example, the display area MG-1 of the LD block ID for uniquely identifying the LD block, and the display of the symbol name of the gene to which the LD block belongs Area MG-2, display area MG-3 of the number of trials when applying the permutation method, and display area MG- of the number of times (Reach) a value greater than a certain likelihood is obtained as a result of the permutation method 4, the display area MG-5 of the P value (asyP: asymmetric to P) calculated asymptotically following the chi-square distribution, and the P value by the permutation method (empP: empirical) P) display area MG-6, SNP total display area MG-7, haplotype total display area MG-8, and target LD block Display area MG-9 of the number of SNPs (significant SNP number) and the total number of SNPs that were 5% significant in the single point analysis among the SNP groups to be collected, and a list of SNP groups (SNPs) included in the target LD block List display area MG-10, case group number (case) display area MG-11, control group number (control) display area MG-12, and diplotype type was not uniquely determined The display area MG-13 of the number of samples removed from the test object for reasons such as the above, and the display area MG-14 of the total number of cases and controls (case + control) are configured.
[0209]
In the display area MG-10 of the SNP list, “*” marks are given to SNPs that are 5% significant by single point analysis.
[0210]
Here, for example, when the LD block ID which is the first data in this figure is “YA-003.CC376-101402.AP1G1.T002223.T002428”, the gene name to which the LD block belongs is “**”, and permutation It is shown that the number of trials when applying the method is “220,000” and the number of times that a value equal to or greater than a certain likelihood value is obtained by the result of permutation is “0”.
[0211]
Subsequently, the P value (asyP: asymptotic P) calculated on the assumption that the statistic used for likelihood calculation asymptotically follows the chi-square distribution is “0”, and the P value by the permutation method (empP: Empirical P) is “ 0, the number of SNPs included in the LD block (#snp) is “3”, and the number of haplotypes (#haplotype) of the LD block is “4”.
[0212]
Subsequently, among the SNP groups included in the LD block, the number of SNPs (# positive | #hap) that was 5% significant in the single-point SNP analysis is “one of three SNPs (1 | 3)”, It is indicated that the list of SNPs (SNPlists) included in the LD block is “T002223, T002429, T002428”.
[0213]
In addition, the number of cases (case) is “148”, the number of controls (control) is “227”, the diplotype type is not uniquely determined, etc., and the number of samples that are not subject to testing is “1”. It is indicated that the total number of cases and controls (case + control) as a target is “375”.
[0214]
In addition, “*” attached to “T002429” in the display area MG-10 of the SNP list indicates that the single point analysis was significant by 5%.
[0215]
[Other embodiments]
Although the embodiments of the present invention have been described so far, the present invention can be applied to various different embodiments in addition to the above-described embodiments within the scope of the technical idea described in the claims. May be implemented.
[0216]
For example, the case where the haplotype analysis apparatus 100 performs processing in a stand-alone form has been described as an example. However, processing is performed in response to a request from a client terminal configured in a separate housing from the haplotype analysis apparatus 100, and the processing You may comprise so that a result may be returned to the said client terminal.
[0217]
In addition, among the processes described in the embodiment, all or part of the processes described as being automatically performed can be performed manually, or all of the processes described as being performed manually are all performed. Alternatively, a part can be automatically performed by a known method.
[0218]
In addition, the processing procedures, control procedures, specific names, information including parameters such as various registration data and search conditions, screen examples, and database configurations shown in the above documents and drawings, unless otherwise specified. It can be changed arbitrarily.
[0219]
Further, regarding the haplotype analysis apparatus 100, each illustrated component is functionally conceptual and does not necessarily need to be physically configured as illustrated.
For example, the processing functions of each part or each device of the haplotype analysis apparatus 100, particularly the processing functions performed by the control unit 102, are all or part of the processing functions performed by a CPU (Central Processing Unit) and the CPU. It can be realized by a program to be interpreted and executed, or can be realized as hardware by wired logic. The program is recorded on a recording medium to be described later, and is mechanically read by the haplotype analyzer 100 as necessary.
[0220]
That is, in the storage unit 106 such as a ROM or an HD, a computer program for giving instructions to the CPU and performing various processes in cooperation with an OS (Operating System) is recorded. The computer program is executed by being loaded into a RAM or the like, and constitutes the control unit 102 in cooperation with the CPU. The computer program may be recorded in an application program server connected to the haplotype analysis apparatus 100 via an arbitrary network 300, and may be downloaded in whole or in part as necessary. is there.
[0221]
The program according to the present invention can also be stored in a computer-readable recording medium. Here, the “recording medium” is an arbitrary “portable physical medium” such as a flexible disk, a magneto-optical disk, a ROM, an EPROM, an EEPROM, a CD-ROM, an MO, and a DVD, and is incorporated in various computer systems. Program in a short time, such as a communication line or carrier wave when transmitting a program via any “fixed physical medium” such as ROM, RAM, HD, or a network such as LAN, WAN, or the Internet The “communication medium” that holds
[0222]
The “program” is a data processing method described in an arbitrary language or description method, and may be in any format such as source code or binary code. The “program” is not necessarily limited to a single configuration, but is distributed in the form of a plurality of modules and libraries, or in cooperation with a separate program represented by an OS (Operating System). Including those that achieve the function. Note that a well-known configuration and procedure can be used for a specific configuration for reading a recording medium, a reading procedure, an installation procedure after reading, and the like in each device described in the embodiment.
[0223]
Various files and the like (SNP sample file 106a to comparison analysis result file 106i) stored in the storage unit 106 are storage means such as a memory device such as a RAM and a ROM, a fixed disk device such as a hard disk, a flexible disk, and an optical disk. Various programs, tables, files, databases, web page files, etc. used for various processes and website provision are stored.
[0224]
The haplotype analysis apparatus 100 connects a peripheral device such as a printer, a monitor or an image scanner to an information processing apparatus such as an information processing terminal such as a known personal computer or workstation, and applies the method of the present invention to the information processing apparatus. You may implement | achieve by mounting the software (a program, data, etc.) to implement | achieve.
[0225]
Furthermore, the specific form of distribution / integration of the haplotype analysis apparatus 100 is not limited to that shown in the figure, and all or part of the haplotype analysis apparatus 100 is functionally or physically distributed / integrated in arbitrary units according to various loads. Can be configured. For example, each database may be independently configured as an independent database device, and a part of the processing may be realized by using CGI (Common Gateway Interface).
[0226]
The network 300 has a function of connecting the haplotype analysis apparatus 100 and the external system 200 to each other. For example, the Internet, an intranet, a LAN (including both wired and wireless), a VAN, and a personal computer communication Networks, public telephone networks (including both analog and digital), leased line networks (including both analog and digital), CATV networks, IMT2000 systems, GSM systems, PDC / PDC-P systems, etc. It may include any of a circuit switching network / portable packet switching network, a wireless paging network, a local wireless network such as Bluetooth, a PHS network, a satellite communication network such as CS, BS, or ISDB. That is, this system can transmit and receive various data via any network regardless of wired or wireless.
[0227]
【The invention's effect】
As described above in detail, according to the present invention, a linkage disequilibrium site is extracted from SNP sample data, a diplotype type is determined for the extracted linkage disequilibrium site, and a haplotype ID is determined for the determined diplotype type. The SNP sample data is divided into a case group and a control group based on specific index information, and each of the divided case group and control group is divided into all linkage disequilibrium sites. The group of corresponding diplotype haplotype IDs is regarded as a multi-value single marker expressing multiple loci genotypes, and genetic heterogeneity is tested. For all SNPs, divided case groups and Since the genetic heterogeneity test is performed on the binary single marker representing the allele type of the control group, and the results of both tests are compared and analyzed, Haplotype analysis apparatus capable of enhancing the constant of the degree of freedom is reduced assay results accuracy, and can provide a program for causing to execute a haplotype analysis methodologies to computers.
[0228]
In addition, according to the present invention, since the haplotype frequency is predicted by combining the case group and the control group, the haplotype analysis apparatus and the haplotype analysis method can be executed by the computer because the sample size is large and accurate prediction is possible. A featured program can be provided.
[0229]
In addition, according to the present invention, a genetic heterogeneity test can be applied in a common input format for both single-point analysis and haplotype analysis, so a haplotype analysis apparatus that can be used for mass analysis, and A program characterized by causing a computer to execute a haplotype analysis method can be provided.
[0230]
In addition, according to the present invention, since the low frequency haplotype (minor haplotype) is not cut off in order to improve the accuracy of the test, it is possible to avoid the risk of missing a disease in which the minor haplotype plays an important role. A program characterized by causing a computer to execute a haplotype analysis apparatus and a haplotype analysis method can be provided.
[0231]
Further, according to the present invention, the posterior probability of the diplotype type is estimated for the linkage disequilibrium site, the estimated posterior probability is compared with a predetermined threshold, and the diplotype type is determined for the linkage disequilibrium site according to the comparison result. Therefore, it is possible to provide a haplotype analysis apparatus that can determine a diplotype type of an individual almost uniquely and a program that causes a computer to execute a haplotype analysis method.
[0232]
In addition, according to the present invention, since the permutation test using the maximum likelihood ratio is used for the 2 × m contingency table, the test table is sparse (including many: zero) and the number of haplotypes increases. In this case, it is possible to provide a haplotype analysis apparatus that can accurately perform chi-square approximation and a program that causes a computer to execute a haplotype analysis method.
[0233]
Furthermore, according to the present invention, SNPs that are significant from the results of the SNP test are extracted, SNPs that constitute a diplotype that is significant from the results of the linkage disequilibrium site test are extracted, and the results of both extractions are extracted. Since it is output in a list format, by comparing the results of single point analysis and haplotype analysis with each other, which SNP in the haplotype was significant at a single point, what kind of effect the combination of SNPs has on what disease It is possible to provide a program characterized by causing a computer to execute a haplotype analysis method and a haplotype analysis method that can infer whether or not it is caused.
[Brief description of the drawings]
FIG. 1 is a flowchart showing the basic principle of the present invention.
FIG. 2 is a block diagram showing an example of the configuration of the system to which the present invention is applied.
FIG. 3 is a block diagram illustrating an example of a configuration of a diplotype type determination unit 102b of the present system to which the present invention is applied.
FIG. 4 is a block diagram showing an example of the configuration of a comparative analysis unit 102g of the present system to which the present invention is applied.
FIG. 5 is a diagram illustrating an example of information stored in an SNP sample file 106a.
FIG. 6 is a diagram illustrating an example of information stored in a case control classification result file 106b.
FIG. 7 is a diagram illustrating an example of information stored in a case control information file 106c.
FIG. 8 is a diagram illustrating an example of information stored in an LD block management file 106d.
FIG. 9 is a diagram showing an example of information stored in a diplotype management file 106e.
FIG. 10 is a diagram illustrating an example of information stored in a haplotype ID set file 106f.
FIG. 11 is a diagram showing an example of information stored in a linkage disequilibrium site test result file 106g.
FIG. 12 is a diagram showing an example of information stored in an SNP test result file 106h.
FIG. 13 is a diagram illustrating an example of information stored in a comparative analysis result file 106i.
FIG. 14 is a flowchart showing an example of main processing of the system in the present embodiment.
FIG. 15 is a flowchart showing an example of a diplotype type determination process of the system according to the present embodiment.
FIG. 16 is a flowchart showing an example of genetic heterogeneity test processing of the system in the present embodiment.
FIG. 17 is a flowchart showing an example of comparative analysis processing of the system in the present embodiment.
FIG. 18 is a diagram illustrating an example of the flow of an analysis system in the present embodiment.
FIG. 19 is a flowchart showing an example for simultaneously executing a large amount of haplotype analysis and single point analysis in the present embodiment.
FIG. 20 is a diagram illustrating an example of typing results and case control information in the embodiment.
FIG. 21 is a diagram showing an example of an estimation result of an individual diplotype type in the present example.
FIG. 22 is a diagram illustrating an example of assigning a haplotype ID in the present embodiment.
FIG. 23 is a diagram illustrating an example of a determination result of a diplotype number in the embodiment.
FIG. 24 is a diagram showing an example of a result of permutation test by an FPMP program in the present example.
FIG. 25 is a diagram illustrating an example of a result of mass analysis by an FPMP program according to the present embodiment.
FIG. 26 is a diagram showing an example in which the results of single-point SNP analysis and haplotype analysis in this example are output in a list format.
[Explanation of symbols]
100 Haplotype analyzer
102 Control unit
102a Linkage disequilibrium site extraction part
102b Diplotype type determination unit
102c Haplotype ID group storage unit
102d Dividing part
102e Linkage disequilibrium site test part
102f SNP test department
102g Comparative analysis unit
102h posterior probability estimation unit
102i posterior probability comparison unit
102j Significant SNP extractor
102k Significant diplotype extractor
102m list format output section
104 Communication control interface unit
106 Storage unit
106a SNP sample file
106b Case control classification result file
106c Case control information file
106d LD block management file
106e Diplotype management file
106f Haplotype ID set file
106g Linkage disequilibrium site test result file
106h SNP test result file
106i comparative analysis result file
108 Input / output control interface
112 Input device
114 output device
200 External system
300 network

Claims (8)

A haplotype analysis device including at least a storage unit, a control unit, and an output device,
The storage unit
SNP sample data storage means for storing SNP sample data configured by associating a sample ID for uniquely identifying a sample, a SNP ID for uniquely identifying a SNP, and a genotype of the SNP ,
Disease index information storage means for storing the sample ID, the SNPID, and disease index information indicating a disease index in association with each other;
With
The control unit
Linkage disequilibrium site extraction means for extracting linkage disequilibrium sites from the SNP sample data stored in the SNP sample data storage means ;
A diplotype type determining means for determining a diplotype type for the linkage disequilibrium site extracted by the linkage disequilibrium site extracting means;
A haplotype ID set storage unit that associates a set of haplotype IDs with respect to the diplotype type determined by the diplotype type determination unit and stores it in the storage unit;
Dividing means for dividing the SNP sample data stored in the SNP sample data storage means, in case and control groups based on specific the disease index information stored in the disease index information storage unit,
For all of the linkage disequilibrium region, representing a plurality locus of the genotype of a set of the diplotype type of the haplotypes ID corresponding to each of the divided the case group and the control group by the dividing means Linkage disequilibrium site test means for testing genetic heterogeneity by considering it as a multi-value single marker;
SNP test means for testing genetic heterogeneity for all single SNPs for binary single markers representing allele types of the case group and the control group divided by the division means;
Comparative analysis means for associating the test result by the linkage disequilibrium site test means with the test result by the SNP test means and outputting to the output device in association with each other ,
A haplotype analyzer characterized by comprising: The diplotype type determining means is:
A posteriori probability estimating means for estimating the diplotype posterior probability for the linkage disequilibrium site;
Posterior probability comparing means for comparing the posterior probability estimated by the posterior probability estimating means with a predetermined threshold;
Further comprising
Determining the diplotype type for the linkage disequilibrium site according to the comparison result by the posterior probability comparison means,
The haplotype analysis apparatus according to claim 1. The above genetic heterogeneity test is:
Using a permutation test with a maximum likelihood ratio for a 2 × m contingency table,
The haplotype analyzer according to claim 1 or 2, characterized in that: The comparative analysis means is
Significant SNP extracting means for extracting SNPs that were significant from the test result by the SNP test means;
Significant diplotype extracting means for extracting SNPs constituting the diplotype that were significant as a result of the test by the linkage disequilibrium site test means;
A list format output means for outputting the extraction result by the significant SNP extraction means and the extraction result by the significant diplotype extraction means in a list format;
The haplotype analyzer according to any one of claims 1 to 3, further comprising: A program for executing a haplotype analysis method to be executed in a haplotype analysis apparatus including at least a storage unit, a control unit, and an output device,
The storage unit
SNP sample data storage means for storing SNP sample data configured by associating a sample ID for uniquely identifying a sample, a SNP ID for uniquely identifying a SNP, and a genotype of the SNP ,
Disease index information storage means for storing the sample ID, the SNPID, and disease index information indicating a disease index in association with each other;
With
Executed in the control unit,
A linkage disequilibrium site extracting step for extracting a linkage disequilibrium site from the SNP sample data stored in the SNP sample data storage means ;
A diplotype type determination step for determining a diplotype type for the linkage disequilibrium site extracted in the linkage disequilibrium site extraction step;
A haplotype ID set storage step that associates a set of haplotype IDs with respect to the diplotype type determined in the diplotype type determination step and stores them in the storage unit ;
A dividing step of dividing the SNP sample data stored in the SNP sample data storage means, in case and control groups based on specific the disease index information stored in the disease index information storage unit,
For all of the linkage disequilibrium region, representing the genotype of the dividing said case group divided by step and the diplotypes mold set multiple loci of the haplotypes ID corresponding to each of the control group Linkage disequilibrium site test step for testing genetic heterogeneity as a multi-value single marker,
A SNP test step for testing genetic heterogeneity for all single SNPs for binary single markers representing allele types of the case group and the control group divided by the division step;
A comparative analysis step of associating the test result of the linkage disequilibrium site test step with the test result of the SNP test step and outputting the result to the output device ;
Program characterized and son-in-law contains a. The above diplotype type determination step is:
A posteriori probability estimating step for estimating the diplotype posterior probability for the linkage disequilibrium site;
A posterior probability comparison step for comparing the posterior probability estimated in the posterior probability estimation step with a predetermined threshold;
Further including
Determining the diplotype type for the linkage disequilibrium site according to the comparison result of the posterior probability comparison step;
The program according to claim 5. The above genetic heterogeneity test is:
Using a permutation test with a maximum likelihood ratio for a 2 × m contingency table,
The program according to claim 5 or 6. The comparative analysis step is
A significant SNP extraction step of extracting SNPs that were significant from the test result of the SNP test step;
A significant diplotype extraction step for extracting SNPs constituting the diplotype that were significant by the test result in the linkage disequilibrium site test step;
A list format output step for outputting in a list format the extraction result of the significant SNP extraction step and the extraction result of the significant diplotype extraction step;
The program according to claim 5, further comprising:

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