JP7328632B2 - Manufacturing device, manufacturing method, program, and recording medium for integrated set data - Google Patents

Description

The present invention relates to an integrated set data manufacturing apparatus, manufacturing method, program, and recording medium.

Genome sequences such as DNA have various different mutations, for example, between species, between races, between individuals, etc., and these mutations are considered to be involved in some traits. Among them, most of the single nucleotide polymorphisms (SNPs) are in linkage disequilibrium in which correlations between alleles are maintained, so analysis of linkage disequilibrium is very important. As a method for analyzing linkage disequilibrium, for example, a method is known in which, for a large number of mutations present in a genome sequence, the relationship between each mutation is sequentially calculated in a pyramidal fashion. (Non-Patent Document 1).

Lynn M Beris et al., Journal of human genetics, 57, 18-25 (2012)

However, this method must compute N×N individual relationships, for example, if there are N mutations. Therefore, the computation becomes more explosive as the number of mutations increases. Also, according to this method, N×N squares are piled up in a pyramid shape, and each square indicates a calculation result. However, even if the calculation result is shown for each cell, it is difficult to visually read the meaning indicated by it, that is, the relationship regarding linkage disequilibrium between mutations, from the display. It is also difficult to

Therefore, it is an object of the present invention to provide a new data production apparatus for mutations, which can easily read relationships such as linkage disequilibrium between mutations even if the number of mutations increases. .

In order to achieve the above object, the integrated set data manufacturing apparatus of the present invention comprises:
including an acquisition portion, a scanning portion, and an accumulation portion;
The acquisition unit
obtaining a reference sequence and a plurality of sample sequences of a group of samples;
The reference sequence is a sequence in which nucleic acid information is arranged corresponding to each consecutive position,
The sample sequence is a sample sequence of each sample contained in the sample group, and is a sequence in which nucleic acid information is arranged corresponding to each consecutive position of the reference sequence,
The scanning unit
Regarding the sample sequences of the sample group, the nucleic acid information of each position is put together into one set, and the presence or absence of mutation with respect to the nucleic acid information of the reference sequence is indicated for each position set from the upstream side to the downstream side. scanning mutation patterns,
The stacking unit is
sequentially determining whether or not the upstream set and the downstream set satisfy the integration condition in the scanning;
if the aggregation condition is satisfied, add the downstream set to the upstream set to form an aggregated set containing a plurality of sets;
if the accumulation condition is not met, stop adding downstream sets;
A set that is not added to the set on the upstream side and that is not added to the set on the downstream side is regarded as a single accumulated set,
The accumulation condition is a condition based on the commonality of mutation patterns regarding arbitrary relational information between positions,
It is characterized in that, by the accumulation and aggregation of the accumulation unit, the accumulation set data is produced in which the relationship of the relational information between the positions of the specimen group is expressed as the accumulation set.

The method for producing aggregated set data of the present invention includes:
comprising an acquisition step, a scanning step, and an integration step;
The obtaining step includes
obtaining a reference sequence and a plurality of sample sequences of a group of samples;
The reference sequence is a sequence in which nucleic acid information is arranged corresponding to each consecutive position,
The sample sequence is a sample sequence of each sample contained in the sample group, and is a sequence in which nucleic acid information is arranged corresponding to each consecutive position of the reference sequence,
The scanning step includes
Regarding the sample sequences of the sample group, the nucleic acid information of each position is put together into one set, and the presence or absence of mutation with respect to the nucleic acid information of the reference sequence is indicated for each position set from the upstream side to the downstream side. scanning mutation patterns,
The accumulating step includes:
sequentially determining whether or not the upstream set and the downstream set satisfy the integration condition in the scanning;
if the aggregation condition is satisfied, add the downstream set to the upstream set to form an aggregated set containing a plurality of sets;
if the accumulation condition is not met, stop adding downstream sets;
A set that is not added to the set on the upstream side and that is not added to the set on the downstream side is regarded as a single accumulated set,
The accumulation condition is a condition based on the commonality of mutation patterns regarding arbitrary relational information between positions,
The accumulation set data in which the relationship of the relationship information between the positions of the specimen group is expressed as the accumulation set is produced by the accumulation set in the accumulation step.

A program according to the present invention causes a computer to execute the method for producing aggregated set data according to the present invention.

The recording medium of the present invention is computer-readable, recording the program of the present invention.

According to the method of the present invention, unlike the pyramidal analysis described above, the sequence of the sample group is scanned from the upstream side to the downstream side for the mutation pattern of each mutation position set, and the distance between the sets is Depending on whether or not the accumulation condition for linkage disequilibrium is satisfied, the set indicating linkage disequilibrium can be aggregated (blocked). That is, for example, when a set of mutation positions that are in linkage disequilibrium are continuously detected, they are accumulated, and when a set of mutation positions that are not in linkage disequilibrium are detected, accumulation is stopped. In this way, it is possible to sequentially obtain aggregated set data in which mutation positions having a certain degree of linkage disequilibrium are blocked. For this reason, for example, even if the number of mutation positions increases, it is possible to easily accumulate and aggregate them in sequence, and through accumulation and aggregation, the linkage disequilibrium relationship between the positions of the sample group can be visualized. You can also Therefore, according to the present invention, it is possible to easily determine the relationship between positions in a sample group with respect to various relational information such as linkage disequilibrium.

FIG. 1 is a block diagram showing an example of a manufacturing apparatus according to Embodiment 1. FIG. FIG. 2 is a block diagram showing an example of the hardware configuration of the manufacturing apparatus according to the first embodiment; FIG. 3 is a flow chart showing an example of the manufacturing method of the first embodiment. FIG. 4 is a schematic diagram showing an example of extraction of mutation patterns of reference sequences and sample sequences of a sample group according to Embodiment 1. FIG. FIG. 5 is a schematic diagram showing an example of aggregation in the first embodiment. FIG. 6 is a flow chart showing another example of the manufacturing method of the first embodiment. FIG. 7 is a schematic diagram showing another example of aggregation in Embodiment 1. FIG. FIG. 8 is a schematic diagram showing an example of connection aggregation in the first embodiment. FIG. 9 is a schematic diagram showing another example of aggregation in the fourth embodiment. FIG. 10 is a schematic diagram showing another example of aggregation in the fourth embodiment. FIG. 11 is a schematic diagram showing an example of the classification of a sample group into subgroups and its taxonomic group mutation pattern in Embodiment 5. FIG. FIG. 12 is a schematic diagram showing another example of aggregation in the first embodiment.

In the present invention, a "sequence" is sequence information relating to a nucleic acid of an organism. In the present invention, the term "reference sequence" is not particularly limited, and is a reference sequence for comparison with specimen sequences, and may be sequence information on nucleic acids of any species. A "specimen group" is a group composed of a plurality of specimens, and a "specimen sequence" is sequence information of each specimen that constitutes the specimen group. The type of sample is not particularly limited, and can be arbitrarily selected by the user, for example. The number of specimens in the specimen group is not particularly limited, and is one or more, preferably two or more. Specifically, the lower limit of the number is, for example, 2 or more and 10 or more, and the upper limit of the number is not particularly limited. It is possible.

The type of the sequence is not particularly limited as long as it is a sequence in which nucleic acid information is aligned corresponding to each of consecutive positions. The length of the array is not particularly limited, and processing of lengths such as 1000 orders, 10000 orders, or longer can be performed by using a processor or the like to be described later. "Positions" can, for example, be represented by consecutive numbers, for example, position 1, position 2, position 3, etc. when 20 positions are consecutive.

In the sequence, the nucleic acid information corresponding to the position is not particularly limited, and examples thereof include nucleic acid bases. When the nucleic acid information is the bases, the sequence is a base sequence of consecutive bases. In this case, the base sequence includes, for example, sequences of DNA, RNA, and the like. The base sequence is represented by a sequence of bases, but the sequence is not particularly limited and can be appropriately set according to the purpose. That is, the alignment may be, for example, alignment based on physical distance, such as sequences determined by sequencing, alignment based on genetic distance reflecting recombination, etc., or genome-wide association analysis. (GWAS) may be arranged according to the order of statistical significance. The nucleic acid information is not limited to this, and may be numerical information such as the number of consecutive identical bases, the number of consecutive identical motif sequences, and the like. When the nucleic acid information is the number information, the sequence is a sequence of consecutive numbers.

In the present invention, the type and arrangement format of the nucleic acid information of the reference sequence and the sample sequence are not particularly limited.

In the present invention, the term "mutation" has a broad meaning and means that the sample sequence exhibits different nucleic acid information from the reference sequence at the corresponding position. When the sequence is the base sequence, for example, the nucleic acid information at a position of the reference sequence is "A", while the nucleic acid information at the same position of the sample sequence is "T", "C", " G", etc., the nucleic acid information of the sample sequence can be said to be a narrowly defined mutation, that is, a mutation having a genotype (allele) different from that of the reference sequence. Further, when the array is the numerical array, for example, the numerical information at a certain position of the reference array is "4", while the numerical information at the same position of the sample array is "1" and "2". , "3", etc., it can be said that the numerical information of the specimen sequence is a mutation. In the present invention, as will be described later, for example, for a specimen sequence having different nucleic acid information at the corresponding position with respect to the reference sequence, the relationship of the relationship information between the positions is extracted, so that the position is a mutation Also called position.

In the present invention, the "relationship information" is not particularly limited, for example, it is an object of the relationship between the positions of the specimen group to be analyzed, and specific examples include linkage disequilibrium within the same chromosome, chromosome Gamete disequilibrium that straddles the Said linkage disequilibrium is, for example, a correlation between two mutation positions.

An embodiment of the present invention will be described. The invention is not limited to the following embodiments. In each figure below, the same reference numerals are given to the same parts. Also, the descriptions of the respective embodiments can be referred to each other's description unless otherwise specified. Furthermore, the configuration of each embodiment can be combined unless otherwise specified. For convenience of explanation, the reference sequence and the sample sequence will be described below as examples of sequences determined by sequencing, that is, sequences showing alignment based on physical distances.

[Embodiment 1]
FIG. 1 is a block diagram showing the configuration of an example of an integrated set data manufacturing apparatus (manufacturing apparatus) according to the present embodiment. As shown in FIG. 1 , the manufacturing apparatus 10 has an acquisition section 11 , a scanning section 12 and an accumulation section 13 . For example, the manufacturing apparatus 10 may further have an output section 14 and may have a connecting section 15 . A form having the connecting part 15 will be described later in the second embodiment. The manufacturing apparatus 10 is also called a manufacturing system, for example. The manufacturing apparatus 10 may be, for example, a single apparatus including the respective units, or may be an apparatus in which the respective units are connectable via a communication network.

The communication network is not particularly limited, and a known communication network can be used, and may be wired or wireless. The communication network includes, for example, the Internet line, telephone line, LAN (Local Area Network), WiFi (Wireless Fidelity), and the like. The processing of each part of the manufacturing apparatus 10 may be performed on the cloud.

The acquisition unit 11 acquires the reference sequence and a plurality of sample sequences of the sample group. The acquisition method of the reference sequence and the sample sequence by the acquisition unit 11 is not particularly limited. may receive. In addition, the manufacturing apparatus 10 stores, for example, various reference sequences and a plurality of specimen arrays in the storage device 107, and stores a target reference sequence and a plurality of specimen arrays (specimen arrays of a specimen group) as necessary. , may be selected and acquired by the acquisition unit 11 . As a result, it is possible to analyze a specimen group in which various specimens are combined.

The scanning unit 12 collects the nucleic acid information of each position of the sample sequence of the sample group into one set (also referred to as one set), and from the upstream side to the downstream side, for each position set, the above A mutation pattern that indicates the presence or absence of mutations in the nucleic acid information of the reference sequence is scanned.

In the scanning, the stacking unit 13 sequentially determines whether or not the upstream set and the downstream set satisfy the stacking condition. The determination by the stacking unit 13 can be performed in parallel with the scanning by the scanning unit 12, for example. In the determination, if the upstream set and the downstream set satisfy the accumulation condition, the downstream set is added to the upstream set to form an accumulated set containing a plurality of sets, satisfying the accumulation condition. If not, stop adding downstream sets. In addition, when the upstream set and the downstream set do not satisfy the accumulation condition, a set that is not added to the upstream set and to which the downstream set is not added is regarded as a single accumulated set. do. The latter set, to which no set is added, is also called a single set because it remains a single set. The aggregate grouping is also called blocking, and the aggregate group is also called a block. When the relationship information is linkage disequilibrium, the aggregated set is also called, for example, a linkage disequilibrium block (LD block).

By such aggregation and aggregation, it is possible to produce aggregate set data in which the relationship of the relationship information between the positions of the specimen group is expressed as the aggregate set. Aggregation and grouping can also be called blocking, for example. That is, in the present invention, if each set is a set that indicates the relationship of the relational information, the blocks are formed by adding the set, and if there is no set that indicates the relation of the relational information, It is blocked as a single aggregate set. Therefore, for each position of the specimen group, it is possible to generate data divided into blocks called accumulated sets, which indicate the relationship with respect to the relationship information. According to the aggregate set data, it is possible to easily visually determine, for example, a set indicating relevance with respect to the relationship information only by the aggregate set.

The output unit 14 outputs integrated set data in which the integrated set is expressed as a block with respect to the position of the sample array of the sample group. The output of the data may be, for example, display on a display 105, which will be described later, or output to the external device via the communication network by the communication device 106, which will be described later.

Next, FIG. 2 illustrates a block diagram of the hardware configuration of the manufacturing apparatus 10. As shown in FIG. The manufacturing apparatus 10 includes, for example, a CPU (Central Processing Unit) 101, a memory 102, a bus 103, an input device 104, a display 105, a communication device 106, and a storage device 107. Each part of the manufacturing apparatus 10 is connected to each other via a bus 103 by each interface (I/F).

The CPU 101 is a processor responsible for overall control of the manufacturing apparatus 10, and is not limited to a CPU, and may be another processor. In the manufacturing apparatus 10, the CPU 101 executes, for example, the program of the present invention and other programs, and reads and writes various types of information.

The manufacturing apparatus 10 can be connected to a communication network through, for example, a communication device 106 connected to the bus 103, and can also be connected to, for example, an external device via the communication network. The connection method between the manufacturing apparatus 10 and the external device is not particularly limited, and may be wired connection or wireless connection, for example. The wired connection may be, for example, a cord connection or a cable connection for using a communication network. The wireless connection may be, for example, a connection using a communication network or a connection using wireless communication. The communication network is not particularly limited, and for example, a known communication network can be used, which is the same as described above. The external device is not particularly limited, and examples thereof include databases, personal computers (PCs), tablets, smartphones, and the like.

The memory 102 includes, for example, a main memory, which is also referred to as main memory. When the CPU 101 performs processing, for example, the memory 102 reads various programs 108 such as the program of the present invention stored in an auxiliary storage device to be described later, and the CPU 101 receives data from the memory 102, Run program 108 . The main memory is, for example, RAM (random access memory). Memory 102, for example, further includes a ROM (Read Only Memory).

The storage device 107 is also called a so-called auxiliary storage device, for example, in contrast to the main memory (main storage device). The storage device 107 includes, for example, a storage medium and a drive that reads from and writes to the storage medium. The storage medium is not particularly limited, and may be, for example, a built-in type or an external type, and includes HD (hard disk), CD-ROM, CD-R, CD-RW, MO, DVD, flash memory, memory card, and the like. and the drive is not particularly limited. The storage device 107 can also be exemplified by a hard disk drive (HDD) in which a storage medium and a drive are integrated, for example. For example, the storage device 107 stores the program 108 as described above, and the memory 102 reads the operation program 108 from the storage device 107 when the CPU 101 is executed as described above. Further, the storage device 107 may store, for example, information input to the manufacturing apparatus 10, information obtained by the manufacturing apparatus 10, and the like. The storage device 107 may store, for example, various conditions such as the accumulation condition described above and the connection condition described later.

The input device 104 is, for example, a scanner, touch panel, keyboard, or the like. Examples of the display 105 include an LED display and a liquid crystal display.

Next, the manufacturing method of this embodiment will be described as an example using the flow chart of FIG. The manufacturing method of this embodiment can be carried out using, for example, the manufacturing apparatus 10 shown in FIGS. In addition, the manufacturing method of this embodiment is not limited to the use of the manufacturing apparatus 10 .

First, the reference sequence and a plurality of sample sequences of the sample group are acquired in the acquiring step (S101). The above steps can be executed by the acquisition unit 11 of the manufacturing apparatus 10, for example.

Next, in the scanning step, the nucleic acid information at each position of the sample sequence of the sample group is collected into one set, and from the upstream side to the downstream side, the reference sequence for the set of each position is obtained. A mutation pattern indicating the presence or absence of mutation in the nucleic acid information is scanned (S102). The above steps can be performed by the scanning unit 12 of the manufacturing apparatus 10, for example.

Here, FIG. 4 shows an outline of the sample sequences of the reference sequence and the sample group. Each sequence shown in FIG. 4 is not a base sequence of an actual organism, but a pseudo-base sequence of 20 base length set for explanation.

In FIG. 4 (A), the horizontal alignment (row) of the "reference sequence" is a base sequence in which bases are continuous, the bases corresponding to the continuous positions are indicated by circles, and the types of bases ( A, C, G, T). "Positions" are consecutive positions in the reference sequence, and are assigned serial numbers (1 to 20) from the upstream side. “Sample sequences 1 to 5” are sample sequences of five samples included in the sample group. Then, the horizontal arrangement (row) of "specimen sequences 1 to 5" is a base sequence in which bases are continuous so as to correspond to each of the continuous positions (1 to 20) of the reference sequence, and the continuous positions Bases corresponding to are circled. In FIG. 4A, the types of bases in the sample sequence are omitted. In FIG. 4(A), sample sequences 1 to 5 form one set by grouping bases at the same positions. That is, in the case of FIG. 4A, for example, the set of position 1 is represented by the vertical base arrangement (column) of position 1 in the sequences of samples 1, 2, 3, 4, and 5. FIG. A "set" is also called a "set", for example.

"From the upstream side to the downstream side" is not particularly limited, and is, for example, the direction from the 5' side to the 3' side in the sequence. The present invention is not limited to this, and for example, for the sample sequences of the sample group, any one end side may be arbitrarily set as the upstream side and the other end side may be set as the downstream side. Also, "from the upstream side to the downstream side" means scanning in one direction, and the scanning start position is not limited at all. That is, scanning may be performed from the upstream end (position 1), or may be performed from an intermediate position. In FIG. 4, as an example, the left side of the 5' end of the sequence is the upstream side, the right side of the 3' end of the sequence is the downstream side, and scanning from the end is described.

FIG. 4(B) shows an outline of mutation patterns in each set of sample sequences of the sample group. In FIG. 4(B), for each set of sample sequences, bases exhibiting mutations relative to bases at the same position in the reference sequence are indicated by hatched circles. That is, in the case of position 1, the base of the reference sequence is "A", so if the base at position 1 is a mutated base other than "A" for the sample sequences of the sample group, the base is treated as the presence of mutation. is indicated by a hatched circle. Thus, the set of positions 1 is represented as a mutation pattern in which specimens 1 to 3 are circles with the same bases as in the reference sequence, and specimens 4 and 5 are hatched circles. Such mutation patterns are sequentially extracted from each set from the upstream side to the downstream side by the scanning.

Next, the accumulation step sequentially determines whether or not the upstream set and the downstream set satisfy the accumulation condition in the scanning. In the determination, if the accumulation condition is satisfied, the downstream set is added to the upstream set to form an accumulated set containing a plurality of sets, and if the accumulation condition is not satisfied, the downstream set is added. A set that stops, is not added to the upstream set, and is not added to the downstream set, is a single accumulated set. The stacking process can be performed by the stacking unit 13 of the manufacturing apparatus 10, for example.

Specifically, first, an arbitrary upstream set (n) is set (S103), and an adjacent downstream set (n+1) is set (S104). Then, it is determined whether or not the set (n) on the upstream side and the set (n+1) on the downstream side satisfy the accumulation condition (S105). If the accumulation condition is satisfied (YES), the downstream set (n+1) is added to the upstream set (n) to form an accumulated set including a plurality of sets (S106). Subsequently, if there is an adjacent set further downstream (S107, YES), the downstream set (n+2) is set (S104), and the same processing is repeated. Then, if there is no set adjacent to the downstream side (S107, NO), the addition of the set on the downstream side is stopped and the process ends (END).

On the other hand, if the set condition is not satisfied (S105, NO), addition of the set (n+1) on the downstream side is stopped (S108). Then, if there is an adjacent set further downstream (S109, YES), the downstream set whose addition has been stopped is set as a new upstream set (S110), and the downstream adjacent set (n+2 ) is set (S104), and the same processing is repeated. If the addition of the set (n+1) on the downstream side is stopped (S108) and there is no set adjacent to the downstream side (S109, NO), the set on the downstream side whose addition is stopped is a single integrated set. (S111), and ends (END). In this way, in the accumulation step, as long as the upstream set and the downstream set satisfy the accumulation condition, sets are continuously added to generate an accumulated set containing a plurality of sets (block). addition), and the addition of the set on the downstream side is stopped when the accumulation condition is no longer satisfied. Then, when the addition is stopped, the set on the downstream side is newly used as a starting point, and further sets on the downstream side are integrated and aggregated.

The accumulation condition is not particularly limited, and can be appropriately set according to, for example, the type of the relationship information and the degree of relationship to be detected for the relationship information. Common conditions, for example, can be given as the accumulation conditions. The common condition is, for example, that the number of specimens exhibiting mutations in both the upstream set and the downstream set is equal to or greater than a threshold in the comparison between the mutation pattern of the upstream set and the mutation pattern of the downstream set. It is a condition to The number is not particularly limited, and can be arbitrarily set, for example, two or three. For example, when the number is relatively large, the relationship of the related information is detected more severely, and when the number is relatively smaller, the relationship of the related information is more loosely detected.

Here, as a further specific example, FIG. 5 shows an example of clustering in the mutation pattern scanning shown in FIG. 4(B). In this example, the common condition is, for example, the number of specimens exhibiting mutations in both the upstream set and the downstream set in the comparison between the mutation pattern of the upstream set and the mutation pattern of the downstream set is equal to or greater than the threshold value (two).

As shown in FIG. 5, when the mutation patterns of the collection are scanned from the upstream side to the downstream side, the collection at position 2 and the collection at position 1 show similar mutations in specimens 4 and 5. Therefore, the common condition (there are two thresholds) is satisfied. The subsequent set of position 3 also shows mutations in specimens 4 and 5, and thus satisfies the common condition. Therefore, to the set of positions 1, the sets of positions 2 and 3 are added to form an aggregate set. On the other hand, the next set of positions 4 does not satisfy the common condition because only specimen 5 shows mutations. Therefore, the addition of the set of position 4 to the aggregate set containing positions 1-3 is discontinued. Then, the set at position 4 is newly set as the upstream set, but since the number of specimens exhibiting mutation is one, the common condition is not satisfied, and it becomes a single accumulated set. The set of positions 5 is then set as the new upstream set, whereas the set of positions 6 shows similar mutations in specimens 3, 4 and 5, so the common condition is Fulfill. Therefore, the set of positions 6 is added to the set of positions 5 to form an aggregate set. After that, at each position, the processing of aggregation is performed in the same way. In this way, as shown in FIG. 5, the sample arrangement of the sample group is aggregated and grouped to indicate the relationship of the relational information at positions 1 to 20. FIG.

The common condition may be, for example, a condition set only between adjacent upstream sets and downstream sets, or all sets included in an aggregate set and their downstream sets It may be a set condition.

When the common condition is set strictly, for example, by inserting other mutations between the actually related sets, the common condition is not satisfied, and the upstream set is related to the downstream Side sets may not be added. Therefore, the accumulation condition may include, for example, a reserve condition in addition to the common condition. The reserved condition is not particularly limited, and for example, if the downstream set does not satisfy the common condition with respect to the upstream set, the position of the set that satisfies the common condition on the downstream side; It is a condition that the distance from the position of the upstream set is equal to or less than a threshold. The distance is the distance between sets satisfying the common condition (gap between sets), and is, for example, 2 bases, 1 base, or the like.

A flow chart of FIG. 6 shows an example of using the reserved conditions as the manufacturing method of the present embodiment. The flowchart of FIG. 6 is similar to the flowchart of FIG. 3 unless otherwise indicated. As shown in FIG. 6, in determining whether or not the upstream set (n) and the downstream set (n+1) satisfy the accumulation condition (S105), if the accumulation condition is not satisfied (S105, NO). Furthermore, it is determined whether or not the reservation condition is satisfied (S201). If the reservation condition is satisfied (S201, YES), the downstream set (n+1) is added to the upstream set (n) to form an integrated set containing a plurality of sets (S106). On the other hand, if the reservation condition is not satisfied (S201, NO), addition of the set (n+1) on the downstream side is stopped (S108), and the same processing is performed thereafter.

Here, as a further specific example, FIG. 7 shows an example of clustering in the mutation pattern scanning shown in FIG. 4(B). In this example, the common condition is, for example, the number of specimens exhibiting mutations in both the upstream set and the downstream set in the comparison between the mutation pattern of the upstream set and the mutation pattern of the downstream set is a threshold value (two) or more, and the reserved condition is, for example, when the set on the downstream side does not satisfy the common condition, the position of the set that satisfies the common condition on the downstream side and the The distance from the position of the set on the upstream side is assumed to be equal to or less than the threshold value (1 base). That is, the number of bases that do not satisfy the common condition is set as the threshold value (1 base).

When only the common condition is used, 12 aggregate sets are generated for a 20-base-long sequence, as shown in FIG. However, although positions 3 and 5, for example, are separate accumulation sets, their mutation patterns themselves have a very high degree of commonality. Therefore, according to the common condition alone, the mutation pattern of the position 4 set excludes the relationship between the position 3 set and the position 5 set. In such a case, the further use of the reservation condition allows picking up the relationship between position 3 and position 5 into the same aggregation set. That is, as shown in FIG. 7, the set of positions 4 does not satisfy the common condition with respect to the set of positions 3, but the set of positions 5 further downstream does not satisfy the common condition with respect to the set of positions 3. The condition is satisfied and the distance between sets is 1 base at position 4, satisfying the reservation condition. Thus, to the aggregated set of positions 1-3, the set of position 4 is added as a reserved set, and positions 5 and 6 are also added to produce an aggregated set containing positions 1-6. In FIG. 7, the double-headed arrows below the sample array indicate the relationship between positions satisfying the common condition added by the reservation condition.

After the accumulation step, the output step may output accumulated set data in which the accumulated set is represented as a block, for example, with respect to the positions of the sample arrays in the sample group. The aggregate set data is, for example, visually presented data.

As described above, by setting the conditions for accumulation strictly, an accumulation set containing mutation sites that are highly related to each other can be obtained, for example. In this case, for example, many small aggregate sets may be generated. On the other hand, by setting loose accumulation conditions, it is possible to obtain an accumulated set including, for example, mutation positions with low mutual relationships. In this case, for example, a small number of large aggregate sets may be generated. For this reason, for example, by continuously changing the threshold value of the accumulation condition and performing accumulation aggregation for the same sample group a plurality of times, the scale of the accumulation aggregation and the accuracy (resolution) of the relationship are continuously improved. Multiple aggregate set results for each of the aggregation conditions, which are systematically different, can be obtained. It is also possible to display a structured aggregate set by stacking a plurality of aggregate sets for each accumulation condition, for example, in a layered (layered or layered) or recursive (nested) manner. . The structured aggregation set can also have, for example, information on the aggregation boundary accompanying changes in aggregation conditions.

[Embodiment 2]
As shown in FIG. 1, this embodiment illustrates a manufacturing apparatus 10 further having a connecting portion 15 and a manufacturing method having a connecting step.

In the case of performing aggregation and aggregation as in Embodiment 1, an aggregation set that should originally be a single aggregation set is divided by inserting another aggregation set, and each divided range is divided into a plurality of separate , an aggregate set of For example, in FIG. 7 described above, an aggregated set of 1 to 8 is generated from the array of specimen groups of specimens 1 to 5. FIG. However, if we focus only on specimens 3-5, as shown in FIG. 12, positions surrounded by bold lines have mutations, but positions 7-9, 17, 18, and 20 do not. . Therefore, assuming a specimen group consisting of only specimens 3 to 5, aggregated sets 2 and 3 will not be generated. Furthermore, in the case of the specimen group of specimens 3 to 5, since positions 7 to 9 are not included, positions 6 and 11, through position 10, satisfy the reservation condition. Therefore, the originally single aggregated set is divided into aggregated set 1 and aggregated set 5 by aggregated set 2 at position 7, aggregated set 3 at position 8, and aggregated set 4 at position 9 (and position 10). It is understood that For this reason, furthermore, by connecting the above-mentioned aggregated sets that are separated by inserting another aggregated set, for example, the relevance of relational information in a larger range composed of multiple aggregated sets can be extracted. it becomes possible to In this embodiment, such a thing becomes possible by having the connection part 15 or the said connection process.

In the manufacturing apparatus 10 of the present embodiment, the connecting unit 15 determines whether or not non-adjacent accumulated sets satisfy the connecting condition for the accumulated sets obtained by the accumulating unit 13. When the connecting condition is satisfied, the connecting unit 15 accumulates the accumulated sets. Let the set be a connected set. By such linked aggregation, for example, the aggregated set data can be made data representing the relationship of the relational information between the aggregated sets.

In the manufacturing method of the present embodiment, the linking step determines whether non-adjacent integrated sets satisfy a linking condition with respect to the integrated sets obtained in the linking step. Let between is a connected set. The connecting step can be performed by the connecting unit 15 in the manufacturing apparatus 10, for example.

The connection condition is not particularly limited, and for example, a condition that a set of downstream ends of an upstream accumulated set and a set of upstream ends of a downstream accumulated set satisfy the accumulation condition. be done.

Here, as a specific example, FIG. 8 shows an example of linked aggregation for the aggregation set shown in FIG. 4(B). In this example, the common condition in the ligation condition is, for example, mutation in both the upstream set and the downstream set in the comparison between the mutation pattern of the upstream set and the mutation pattern of the downstream set. Assume that the number of specimens to be displayed is equal to or greater than the threshold value (two).

As shown in FIG. 8, between the integrated set 1 and the integrated set 5, integrated sets 2 to 4 are interposed. However, the set at position 6, which is the downstream end of accumulated set 1, and the set at position 11, which is the upstream end of accumulated set 5, have mutations in sample sequences 3, 4, and 5, and the common meet the conditions. Therefore, the aggregated set 1 and the aggregated set 5 can be connected as a connected set. The same is true for the aggregated set 4 and the aggregated set 8, which can be connected as a connected set. In FIG. 8, the lines above the sample array indicate the relationship between the aggregated sets that satisfy the connection conditions, more specifically, the relationship between the positions that satisfy the connection conditions.

In addition to this, the concatenation condition includes, for example, a condition that all pairs of mutation positions straddling both accumulation sets (two accumulation sets) satisfy the accumulation condition. To give a specific example, for example, the aggregate set 1 includes positions 1, 2, 3, 4, 5, and 6, and the aggregate set 5 includes positions 11 and 12. 11, positions 1 and 12, positions 2 and 11, positions 2 and 12, etc., all combinations. And, it is an example of a condition that all pairs of these combinations satisfy the accumulation condition. For example, as described above, when determination is made only at the upstream end and the downstream end, there may be a form that does not satisfy the accumulation condition on the upstream side and downstream side of the connected set to be generated, but all By forming a pair, it is possible to more strictly determine whether or not to connect, so it is possible to reduce the possibility that the accumulation condition is not satisfied on the upstream side and the downstream side of the connected set to be generated.

[Embodiment 3]
In this embodiment, for example, attribute information is used in addition to the sample array as the sample information of the sample group.

In this embodiment, the sample information of the sample group further includes attribute information in addition to the sample sequence. The types of the attribute information are not particularly limited, and include, for example, trait information such as disease, race information, gender information, age information, and the like. The trait information of the disease is, for example, the presence or absence of the disease, a value related to the disease, and the like. It is known that mutations, linkage disequilibrium, etc. in genes may indicate their attributes and associations. For this reason, according to the present embodiment, as in the above-described embodiment, the attribute information is added when the relationship of the nucleic acid information is aggregated and optionally linked from the mutation pattern of the set. allows for further analysis of associations between attributes and mutations.

In the manufacturing apparatus 10 of the present embodiment, the accumulation unit 13 performs accumulation and grouping using the accumulation conditions and attribute conditions. The attribute condition is, for example, a condition that the correlation function between the distribution of the set pattern in the aggregated set and the distribution of the target attribute is maximum. Moreover, in the manufacturing method of the present embodiment, the accumulation step uses the accumulation condition and the attribute condition to perform accumulation and grouping. This step can be performed by the stacking unit 13 of the manufacturing apparatus 10, for example.

In addition, in the manufacturing apparatus 10 of the present embodiment, the linking unit 15 uses the linking condition and the attribute condition to perform linking and grouping. The attribute condition is, for example, a condition that the correlation function between the distribution of mutation patterns in the aggregated set and the distribution of the target attribute is maximum. In the manufacturing method of this embodiment, the linking step uses the linking condition and the attribute condition to perform linking and aggregation. This step can be performed by the connecting unit 15 of the manufacturing apparatus 10, for example.

In each of the above-described embodiments, the nucleic acid information of each position is used for aggregation, but in the present embodiment, the attribute information can also be used for aggregation as described above. That is, for example, it is possible to determine the boundary of the aggregated set so as to optimize a separately set evaluation function (energy function). As the evaluation function, for example, a correlation (relationship) function between the mutation pattern of each sample in a certain aggregate set and the trait information of each sample in the aggregate set is set, and the value of the correlation function is By performing clustering to increase, clusters of mutation sites associated with specific traits can be detected. In that case, a condition for evaluating the correlation (relationship) between the generated accumulated set and the trait is added to the accumulation conditions. According to such a form, the clustering is not performed based only on the mutation pattern of the specimen group, but rather, the clustering set and the clustering set are combined so that the correlation between the generated clustered set and the trait is high. can determine the boundary between In other words, in addition to the relationship between mutation patterns and the relationship between trait information, it is possible to integrate and aggregate the relationship between the former and the latter.

A sample population may include, for example, positive (diseased) and negative (healthy) samples for a disease trait. On the other hand, clustering by mutation patterns alone reflects linkage disequilibrium, for example, but does not reflect traits. For this reason, for example, when the relationship between trait X and linkage disequilibrium is analyzed using aggregation, it is possible that the relationship with the trait cannot be accurately estimated from the results of aggregation based on mutation patterns alone. be done. For this reason, when the analysis of the relationship between traits and linkage disequilibrium is assumed, as in the present embodiment, the specimen sequence and the trait information are further linked as information of each specimen of the specimen group. It is preferred to use Then, in the obtained accumulated set, the accumulated set is adjusted so that the correlation coefficient indicating the relationship between the distribution of the mutation pattern of each specimen and the distribution of the trait (for example, suffering from disease X) of each specimen becomes maximum. It is preferable to carry out conversion. According to such a form, it is possible to assemble weighted mutation patterns of specimens suffering from the disease X. Therefore, based on the results of the obtained accumulated set, for example, it can be estimated that a new specimen may have disease X if it has a similar mutation pattern.

As described above, the trait information is not particularly limited, and includes, for example, nominal attributes (for example, attributes for which magnitude relationships are not defined), and numerical attributes (for example, continuous or discrete attributes for which magnitude relationships are defined). attributes), etc. can be set.

Further, clustering is performed so as to correlate with traits, and from the distribution of mutation patterns in each cluster, the sample group is classified into subgroups having similar mutation patterns based on differences in mutation patterns. good too. Then, for each subgroup, it is also possible to set the frequency of a specific trait value and a specific mutation pattern to be high in the subgroup. In this way, for example, the following evaluations can be made for new specimens. In other words, the novel specimen has unknown trait information, and the same mutation as the specific mutation position included in the accumulated set is known. In this case, by evaluating the degree of association between the mutation pattern of the new specimen and the mutation pattern of each subgroup, it is possible to determine how the new specimen is based on the trait information of the existing specimens included in each subgroup. It becomes possible to presume whether or not an individual has trait characteristics only from the mutation pattern.

[Embodiment 4]
This embodiment is, for example, a form of visualizing the obtained aggregate set data.

The aggregate set data obtained by each of the above-described embodiments can be output as visualized data, for example. An example of this visualization data will be described with reference to the drawings. 9 and 10 show an example of visualized aggregated set data. Each sequence shown in each figure is not an actual base sequence of an organism, but a pseudo base sequence set for explanation. In each figure, the relationship information is linkage disequilibrium, and the relationship is an example evaluated by an index corresponding to the chi-square value between mutation patterns at two mutation positions.

In FIG. 9, the numbers in each column on the left and right ends are the sample numbers (1-10) of the 10 samples, and the information in the horizontal direction of the sample numbers is the base information (mutation) at each position in each sample sequence. , the horizontal information below the sample is the nucleic acid information at each position of the reference sequence. Reference sequence base information is indicated by letters in circles, while sample sequence base information is indicated by letters in circles only for mutations that differ from the reference sequence. In addition, in FIG. 9, the reference sequence is not the entire sequence, but only the mutation positions at which the sample shows mutation in the exon region. The horizontal information below the reference sequence is the position information of the chromosome, and the line connecting the position information of the chromosome and the base information of the reference sequence is the actual physical position in the chromosome for each position of the reference sequence. Show correspondence.

In FIG. 9, in the arrangement of 10 specimens, each rectangular area divided in the vertical direction represents an aggregate set (for example, also referred to as a linkage disequilibrium block). Multiple curves at the top of each rectangular region indicate the relationship between each collection set. The curve can also represent the strength or weakness of the relationship, for example, by color shading, line thickness, line type, and the like. The relationship is, for example, the relationship of the connected sets. One collection set connected by the curve indicates that all collections contained therein are directly or indirectly connected to the other collection set. Then, by tracing the curve that connects them, for example, directly or indirectly connected aggregate sets (connected sets) can be retrieved. As a specific example, for example in FIG. 9, aggregate sets 1, 3, 7, 10, 11, 12, 13, 14, 15, 16, and 17 are interconnected along curves. In other words, in FIG. 9, a linked set composed of a single mutation position within the range of chromosomes in which the clustered set group exists is also displayed at the same time. Therefore, for example, when processing the entire genome, a plurality of such linked sets may be output.

In the tree diagram of FIG. 9, the tree structure connecting the sample numbers on the left end represents the classification of the sample group of samples 1-10 into subgroups based on the mutation pattern. That is, in this tree diagram, the specimens connected by lines form a subgroup. As a specific example, for example, specimens 1 and 6 would be the smallest subgroup, and specimens 1, 6, 2, 8, 5, and 9 would be the larger subgroups.

In FIG. 9, in the upper part of the integrated set of the specimen group, the integrated set is further represented by rectangular areas, and the relationship between the integrated sets is indicated by a combination of straight lines (network paths) connecting the rectangular areas. . This straight line corresponds to the curve showing the relationship described above, but the relationship is expressed by changing the color, thickness, and shape of the line so that the combination of curves does not overlap from upstream to downstream. ing. That is, for example, if the curve connecting the integrated sets is traced from the upstream side, the combination of "integrated set 1→7→11→13→15→17" is extracted. Assuming that this curve has been used, then the combination of "aggregation set 3→7→12" is extracted. Similarly, excluding the curves used in the combination, the combinations of "aggregated set 3→10→13" and "aggregated set 11→14→16" are extracted. The information in the upper row represents each of these combinations by changing the form of the line. Also, the form of the lines may be determined according to the path length of the network, and lines included in the same network are shown in the same color. In addition, for the route of the network, for example, the number of straight lines forming the route may be limited according to arbitrary conditions.

Next, FIG. 10 will be described. In FIG. 10, descriptions of the same notations as in FIG. 9 will be omitted. FIG. 10 is an example of simultaneously displaying a group of aggregate sets that overlap each other in position but are not directly or indirectly connected by the curves showing the relationship between the aggregate sets. For example, in FIG. 10, aggregated sets 25, 27, 30, and 33 are directly or indirectly connected by lines of the same type, thereby indicating the relationship between these aggregated sets. Aggregation sets 1, 3, 4, 6, 8, 12, 13, 14, 15, 16, 17, 19, 21, 22, 24, and 26 similarly have the same connected by lines of a kind. For example, although the two groups of aggregate sets overlap each other in position, it can be read that they are not directly or indirectly connected by the curve showing the relationship between the aggregate sets.

[Embodiment 5]
This embodiment exemplifies, for example, the form of utilization of the integrated set data obtained in each of the above-described embodiments. In the following description, the term "sequence mutation pattern" means a sequence containing mutations in a specimen or the like, and has a different meaning from the "mutation pattern between specimens in a set" in each of the above-described embodiments.

Since DNA sequence mutation patterns correspond to personal information, there are restrictions on the transfer and collection of such patterns. However, not all situations require a pattern of sequence variation with a degree of accuracy or form that identifies an individual. Then, in the analysis, for example, classification information of mutation patterns at multiple mutation positions, that is, subgroups containing multiple mutation patterns with similar sequences instead of strict matches (multiple specimens showing the relationship between mutation and trait information When using the information of the group including), it is considered sufficient to have only information on the relationship with each subgroup, not the mutation pattern of each sequence. Therefore, if each investigator who exchanges information can refer to the mutation pattern of the known sequence, for example, only the results of calculating the information on the relationship with each subgroup for a sample to be evaluated (evaluation sample) By giving and receiving, it is possible to avoid direct giving and receiving of the mutation pattern itself of the sequence of the sample for evaluation.

For the evaluation sample, which is the target of the information to be exchanged, a sequence profile (mutation profile) is generated, for example, by summarizing the frequency of mutations within the same subgroup, rather than the mutation pattern itself of the sequence of the sample within the subgroup. , the evaluation specimen and the subgroup (including a plurality of reference specimens) can be associated via the same profile. Here, the "reference sample" refers to a sample that constitutes the subgroup rather than the reference sequence shown in each of the above-described embodiments.

In addition, it is also possible to specify, for example, a single subgroup (one subgroup) that is most relevant to the evaluation specimen, and exchange information about it. For the evaluation specimen, by specifying the information of association with the subgroup of the reference specimen, for example, the relevant subgroup mutation pattern and accompanying attribute information as the information of the evaluation specimen (Relationships between mutation patterns and disease-related traits, etc.) can also be exchanged. And since it does not correspond to personal information in itself, it is possible to avoid restrictions.

Subgroup information consisting of only a single mutation pattern can be identified as personal information. For this reason, for example, although a subgroup of a sample group contains a mutation pattern similar to that of a specific individual, it contains multiple components, and only the sequence profile (mutation profile, mutation pattern) within the subgroup , it is necessary to make it impossible to determine what kind of mutation pattern is actually formed (anonymization).

In addition, as information that can be used by the practitioner who delivers, for example, the mutation pattern itself of the sequence of the specimen in the subgroup may be shared (published). (also referred to as subgroup sequence profiles or subgroup mutational profiles) may be shared (published). Thereby, the practitioner can, for example, associate the evaluation specimen with the subgroup of the reference specimen via the subgroup mutation pattern (the subgroup mutation profile). The subgroup mutation patterns can be generated, for example, from the mutation patterns of reference sequences contained in the same subgroup.

The practitioner may, for example, classify a plurality of specimens that have been shared (published) in advance as reference specimens into subgroups based on the above-described embodiment, and set the classification result as a "key". . Then, only the conversion information (information on relevance to each taxonomic group) related to the evaluation specimen set separately from the reference specimen by the key may be exchanged. The received transformation information can be used to narrow down the original mutation information within a certain range using the key (classification of reference specimens into subgroups). At that time, the reference sample and its classification information into subgroups can be shared confidentially or publicly shared among a plurality of practitioners. Further, the aforementioned evaluation sample may be, for example, a sample included in a reference sample.

FIG. 11 shows an example in which the five specimens illustrated in FIG. 8 are used as the reference specimens and classified into three subgroups AC. In each sequence in FIG. 11, a hatched circle indicates a mutation that differs from the reference sequence. In FIG. 11, the first row shows the reference sequence, and the fourth row shows the mutation pattern of the sequence of the sample for evaluation. The second row shows the sequence mutation patterns of the reference sample similar to FIG. 8 for each of subgroups A, B and C. FIG. The third level shows the subgroup mutation patterns (mutation profiles) A, B, and C of the subgroups A, B, and C, respectively. The subgroup mutation patterns A, B, and C each represent the union of mutations within the subgroup, that is, information indicating whether or not any of the specimens included in the same subgroup has a mutation. Here, for the sake of simplification, an example is given in which subgroup mutation patterns are generated by paying attention to the presence or absence of mutation at each mutation position. That is, in the case of subgroup mutation pattern A of subgroup A, the position where either specimen 1 or 2 shows mutation is the mutation profile marked with a hatched circle.

Among a plurality of practitioners, for example, if the information of the subgroup in the second row or the subgroup mutation pattern (mutation profile) in the third row is shared in advance, the mutation in the sequence of the evaluation sample in the fourth row Regarding the pattern, information on the relationship with any of the mutation patterns of the sequences of the reference specimens contained in the subgroups A, B, and C, or information on the relationship with any of the subgroup mutation patterns A, B, and C Obtainable. By exchanging only that information, it becomes possible to share the sequence mutation pattern of the evaluation sample and the associated attribute information. Here, since the mutation patterns A to C do not match any of the reference specimens, they do not correspond to personal information, so that restrictions on the transfer of information can be avoided.

[Embodiment 6]
A program of the present embodiment is a program capable of executing the manufacturing method of the present invention on a computer. Alternatively, the program of this embodiment may be recorded on a computer-readable recording medium, for example. The recording medium is not particularly limited, and includes, for example, the above-described storage medium.

Although the present invention has been described with reference to the embodiments, the present invention is not limited to the above embodiments. Various changes that can be understood by those skilled in the art can be made to the configuration and details of the present invention within the scope of the present invention.

<Appendix>
Some or all of the above-described embodiments and examples can be described as in the following appendices, but are not limited to the following.
(Appendix 1)
including an acquisition portion, a scanning portion, and an accumulation portion;
The acquisition unit
obtaining a reference sequence and a plurality of sample sequences of a group of samples;
The reference sequence is a sequence in which nucleic acid information is arranged corresponding to each consecutive position,
The sample sequence is a sample sequence of each sample contained in the sample group, and is a sequence in which nucleic acid information is arranged corresponding to each consecutive position of the reference sequence,
The scanning unit
Regarding the sample sequences of the sample group, the nucleic acid information of each position is put together into one set, and the presence or absence of mutation with respect to the nucleic acid information of the reference sequence is indicated for each position set from the upstream side to the downstream side. scanning mutation patterns,
The stacking unit is
sequentially determining whether or not the upstream set and the downstream set satisfy the integration condition in the scanning;
if the aggregation condition is satisfied, add the downstream set to the upstream set to form an aggregated set containing a plurality of sets;
if the accumulation condition is not met, stop adding downstream sets;
A set that is not added to the set on the upstream side and that is not added to the set on the downstream side is regarded as a single accumulated set,
The accumulation condition is a condition based on the commonality of mutation patterns regarding arbitrary relational information between positions,
An apparatus for producing aggregated aggregated data, wherein the aggregated aggregated data in which the relationship between the positions of the specimen group is expressed as the aggregated aggregated aggregated aggregated data is produced by the aggregation of the aggregated aggregated data by the accumulating unit. .
(Appendix 2)
the accumulation condition is a common condition,
The common condition is that the number of specimens exhibiting mutations in both the upstream set and the downstream set in the comparison between the mutation pattern of the upstream set and the mutation pattern of the downstream set is equal to or greater than a threshold; The manufacturing apparatus according to Supplementary Note 1, wherein the conditions are as follows.
(Appendix 3)
The accumulation conditions further include reservation conditions,
When the set on the downstream side does not satisfy the common condition with respect to the set on the upstream side, the reserved condition is the position of the set that satisfies the common condition on the downstream side and the position of the set on the upstream side. The manufacturing apparatus according to appendix 2, wherein the condition is that the distance between is equal to or less than a threshold value.
(Appendix 4)
further comprising an output section,
4. The manufacturing apparatus according to any one of appendices 1 to 3, wherein the output unit outputs accumulated set data in which the accumulated set is represented as a block for the position of the sample array in the sample group.
(Appendix 5)
further comprising a connector;
The connecting part is
determining whether non-adjacent aggregate sets satisfy a connection condition;
If the connection condition is satisfied, the connection set is defined as a connection set between the collection sets,
The connection condition is a condition that a set of downstream ends of an upstream accumulated set and a set of upstream ends of a downstream accumulated set satisfy the accumulation condition,
5. The manufacturing apparatus according to any one of appendices 1 to 4, wherein the aggregated set data is further data representing the relationship of the relationship information between the aggregated sets by connecting and grouping the connecting parts.
(Appendix 6)
further comprising an output section,
The manufacturing apparatus according to Supplementary Note 5, wherein the output unit outputs integrated set data in which the integrated set is represented as a block and the connected set is represented by a connecting line with respect to the positions of the sample arrays in the sample group. .
(Appendix 7)
7. The manufacturing apparatus according to any one of appendices 1 to 6, wherein the accumulating unit performs a plurality of accumulating groups based on a plurality of different accumulating conditions.
(Appendix 8)
8. The manufacturing apparatus of any one of Appendixes 1 to 7, wherein the arbitrary relationship information between locations is linkage disequilibrium.
(Appendix 9)
The sample information of the sample group includes attribute information in addition to the sample sequence,
The stacking unit is
Aggregation is performed using the aggregation condition and the attribute condition,
9. The manufacturing apparatus according to any one of appendices 1 to 8, wherein the attribute condition is a condition that a correlation function between the distribution of the set pattern in the aggregated set and the distribution of the target attribute is maximum.
(Appendix 10)
The sample information of the sample group includes attribute information in addition to the sample sequence,
The connecting part is
performing concatenation aggregation using the concatenation condition and the attribute condition;
10. The manufacturing apparatus according to any one of appendices 5 to 9, wherein the attribute condition is a condition that a correlation function between the distribution of the mutation pattern in the accumulated set and the distribution of the target attribute is maximum.
(Appendix 11)
comprising an acquisition step, a scanning step, and an integration step;
The obtaining step includes
obtaining a reference sequence and a plurality of sample sequences of a group of samples;
The reference sequence is a sequence in which nucleic acid information is arranged corresponding to each consecutive position,
The sample sequence is a sample sequence of each sample contained in the sample group, and is a sequence in which nucleic acid information is arranged corresponding to each consecutive position of the reference sequence,
The scanning step includes
Regarding the sample sequences of the sample group, the nucleic acid information of each position is put together into one set, and the presence or absence of mutation with respect to the nucleic acid information of the reference sequence is indicated for each position set from the upstream side to the downstream side. scanning mutation patterns,
The accumulating step includes:
sequentially determining whether or not the upstream set and the downstream set satisfy the integration condition in the scanning;
if the aggregation condition is satisfied, add the downstream set to the upstream set to form an aggregated set containing a plurality of sets;
if the accumulation condition is not met, stop adding downstream sets;
A set that is not added to the set on the upstream side and that is not added to the set on the downstream side is regarded as a single accumulated set,
The accumulation condition is a condition based on the commonality of mutation patterns regarding arbitrary relational information between positions,
A method for producing aggregated aggregated data, wherein the aggregated aggregated data is produced in which the relationship of the relationship information between the positions of the specimen group is expressed as the aggregated aggregate by the aggregation in the accumulation step. .
(Appendix 12)
the accumulation condition is a common condition,
The common condition is that the number of specimens exhibiting mutations in both the upstream set and the downstream set in the comparison between the mutation pattern of the upstream set and the mutation pattern of the downstream set is equal to or greater than a threshold; The manufacturing method according to Supplementary Note 11, wherein
(Appendix 13)
The accumulation conditions further include reservation conditions,
When the set on the downstream side does not satisfy the common condition with respect to the set on the upstream side, the reserved condition is the position of the set that satisfies the common condition on the downstream side and the position of the set on the upstream side. 13. The manufacturing method according to appendix 12, wherein the condition is that the distance between is equal to or less than a threshold value.
(Appendix 14)
Furthermore, including an output process,
14. The manufacturing method according to any one of Appendices 11 to 13, wherein the output step outputs integrated set data in which the integrated set is represented as a block for the position of the sample array in the sample group.
(Appendix 15)
further comprising a linking step;
The connecting step includes
determining whether non-adjacent aggregate sets satisfy a connection condition;
If the connection condition is satisfied, the connection set is defined as a connection set between the collection sets,
The connection condition is a condition that a set of downstream ends of an upstream accumulated set and a set of upstream ends of a downstream accumulated set satisfy the accumulation condition,
15. The manufacturing method according to any one of appendices 11 to 14, wherein the aggregated set data is further data representing the relationship of the relational information between the aggregated sets by connecting and grouping in the connecting step.
(Appendix 16)
Furthermore, including an output process,
16. The manufacturing method according to appendix 15, wherein the output step outputs integrated set data in which the integrated set is represented as a block and the connected set is represented by a connecting line with respect to the position of the sample array of the sample group. .
(Appendix 17)
17. The manufacturing method according to any one of appendices 11 to 16, wherein the accumulating step performs a plurality of accumulating groups based on a plurality of different accumulating conditions.
(Appendix 18)
18. A method according to any one of appendices 11 to 17, wherein the arbitrary relationship information between positions is linkage disequilibrium.
(Appendix 19)
The sample information of the sample group includes attribute information in addition to the sample sequence,
The accumulating step includes:
Aggregation is performed using the aggregation condition and the attribute condition,
19. The manufacturing method according to any one of appendices 11 to 18, wherein the attribute condition is a condition that the correlation function between the distribution of the set pattern in the aggregated set and the distribution of the target attribute is maximum.
(Appendix 20)
The sample information of the sample group includes attribute information in addition to the sample sequence,
The connecting step includes
performing concatenation aggregation using the concatenation condition and the attribute condition;
20. The manufacturing method according to any one of Appendices 15 to 19, wherein the attribute condition is a condition that the correlation function between the distribution of the mutation pattern in the accumulated set and the distribution of the target attribute is maximum.
(Appendix 21)
A program for causing a computer to execute the manufacturing method according to any one of appendices 11 to 20.
(Appendix 22)
A computer-readable recording medium recording the program according to appendix 21.

According to the method of the present invention, unlike the pyramidal analysis described above, the sequence of the sample group is scanned from the upstream side to the downstream side for the mutation pattern of each mutation position set, and the distance between the sets is Depending on whether or not the accumulation condition for linkage disequilibrium is satisfied, the set indicating linkage disequilibrium can be aggregated (blocked). That is, for example, when a set of mutation positions that are in linkage disequilibrium are continuously detected, they are accumulated, and when a set of mutation positions that are not in linkage disequilibrium are detected, accumulation is stopped. In this way, it is possible to sequentially obtain aggregated set data in which mutation positions having a certain degree of linkage disequilibrium are blocked. For this reason, for example, even if the number of mutation positions increases, it is possible to easily accumulate and aggregate them in sequence, and through accumulation and aggregation, the linkage disequilibrium relationship between the positions of the sample group can be visualized. You can also Therefore, according to the present invention, it is possible to easily determine the relationship between positions in a sample group with respect to various relational information such as linkage disequilibrium.

10 Manufacturing Apparatus 11 Acquisition Unit 12 Scanning Unit 13 Stacking Unit 14 Output Unit 15 Scanning Unit

Claims (10)

including an acquisition portion, a scanning portion, and an accumulation portion;
The acquisition unit
obtaining a reference sequence and a plurality of sample sequences of a group of samples;
The reference sequence is a sequence in which nucleic acid information is arranged corresponding to each consecutive position,
The sample sequence is a sample sequence of each sample contained in the sample group, and is a sequence in which nucleic acid information is arranged corresponding to each consecutive position of the reference sequence,
The scanning unit
Regarding the sample sequences of the sample group, the nucleic acid information of each position is put together into one set, and the presence or absence of mutation with respect to the nucleic acid information of the reference sequence is indicated for each position set from the upstream side to the downstream side. scanning mutation patterns,
The stacking unit is
sequentially determining whether or not the upstream set and the downstream set satisfy the integration condition in the scanning;
if the aggregation condition is satisfied, add the downstream set to the upstream set to form an aggregated set containing a plurality of sets;
if the accumulation condition is not met, stop adding downstream sets;
A set that is not added to the set on the upstream side and that is not added to the set on the downstream side is regarded as a single accumulated set,
The accumulation condition is a condition based on the commonality of mutation patterns regarding arbitrary relational information between positions,
An apparatus for producing aggregated aggregated data, wherein the aggregated aggregated data in which the relationship between the positions of the specimen group is expressed as the aggregated aggregated aggregated aggregated data is produced by the aggregation of the aggregated aggregated data by the accumulating unit. . the accumulation condition is a common condition,
The common condition is that the number of specimens exhibiting mutations in both the upstream set and the downstream set in the comparison between the mutation pattern of the upstream set and the mutation pattern of the downstream set is equal to or greater than a threshold; 2. The manufacturing apparatus according to claim 1, wherein the condition is that The accumulation conditions further include reservation conditions,
When the set on the downstream side does not satisfy the common condition with respect to the set on the upstream side, the reserved condition is the position of the set that satisfies the common condition on the downstream side and the position of the set on the upstream side. 3. The manufacturing apparatus according to claim 2, wherein the condition is that the distance between is equal to or less than a threshold value. further comprising an output section,
4. The manufacturing apparatus according to any one of claims 1 to 3, wherein said output unit outputs accumulated set data in which said accumulated set is represented as a block for positions of sample arrays in said sample group. further comprising a connector;
The connecting part is
determining whether non-adjacent aggregate sets satisfy a connection condition;
If the connection condition is satisfied, the connection set is defined as a connection set between the collection sets,
The connection condition is a condition that a set of downstream ends of an upstream accumulated set and a set of upstream ends of a downstream accumulated set satisfy the accumulation condition,
5. The manufacturing apparatus according to any one of claims 1 to 4, wherein the aggregated set data is further data representing the relationship of the relationship information between the aggregated sets by connecting and grouping the connecting parts. . further comprising an output section,
6. The manufacturing according to claim 5, wherein the output unit outputs integrated set data in which the integrated set is represented as a block and the connected set is represented by a connecting line with respect to the positions of the sample arrays in the sample group. Device. 7. The manufacturing apparatus according to any one of claims 1 to 6, wherein said accumulating section performs a plurality of accumulating groups based on a plurality of different accumulating conditions. comprising an acquisition step, a scanning step, and an integration step;
The obtaining step includes
obtaining a reference sequence and a plurality of sample sequences of a group of samples;
The reference sequence is a sequence in which nucleic acid information is arranged corresponding to each consecutive position,
The sample sequence is a sample sequence of each sample contained in the sample group, and is a sequence in which nucleic acid information is arranged corresponding to each consecutive position of the reference sequence,
The scanning step includes
Regarding the sample sequences of the sample group, the nucleic acid information of each position is put together into one set, and the presence or absence of mutation with respect to the nucleic acid information of the reference sequence is indicated for each position set from the upstream side to the downstream side. scanning mutation patterns,
The accumulating step includes:
sequentially determining whether or not the upstream set and the downstream set satisfy the integration condition in the scanning;
if the aggregation condition is satisfied, add the downstream set to the upstream set to form an aggregated set containing a plurality of sets;
if the accumulation condition is not met, stop adding downstream sets;
A set that is not added to the set on the upstream side and that is not added to the set on the downstream side is regarded as a single accumulated set,
The accumulation condition is a condition based on the commonality of mutation patterns regarding arbitrary relational information between positions,
A method for producing aggregated aggregated data, wherein the aggregated aggregated data is produced in which the relationship of the relationship information between the positions of the specimen group is expressed as the aggregated aggregate by the aggregation in the accumulation step. . A program for causing a computer to execute the manufacturing method according to claim 8. A computer-readable recording medium recording the program according to claim 9 .

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