JP2001258598A - Method and device for analyzing dna sequence - Google Patents

Abstract

PROBLEM TO BE SOLVED: To improve the accuracy of DNA analysis. SOLUTION: This method for analyzing a DNA sequence, characterized by sequentially sampling a plurality of bases from the DNA sequence at the distance of smaller base number than the base number of a sampling, clustering the sampled words, assuming that the distribution of the words on the galaxy obtained as the result is the characteristics of the DNA sequence, comparing the characteristics of a standard DNA sequence with the DNA sequence of the analysis target to detect inconsistent sections, and consequently detecting an abnormal site in the DNA sequence section.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

The present invention relates to a DNA sequence analysis method and apparatus suitable for analyzing a DNA sequence represented in the form of a base sequence and naturally detecting a mutated portion, an inserted portion and the like.

[0002]

2. Description of the Related Art Conventionally, as a method of analyzing a DNA sequence represented in the form of a base sequence, a method of clarifying the alignment of a DNA sequence using a hidden Markov model or a dynamic programming method is known.

[0003]

However, in the above-mentioned method, the analysis accuracy is low, and the analysis performance with higher accuracy is required.

Accordingly, an object of the present invention is to provide a novel DNA sequence analysis method and apparatus having improved analysis accuracy and a high analysis accuracy.

[0005]

In order to achieve the above object, according to the present invention, a reference DNA sequence is stored in an information processing apparatus, and the DNA sequence to be analyzed is stored in the information processing apparatus. The information processing apparatus sequentially samples a fixed number of base sequences for the reference DNA sequence and the DNA sequence to be analyzed at intervals of a base number smaller than the fixed number, and clusters the sampled base sequences. A distribution state in a galaxy space is acquired, and the distribution of the reference sequence and the distribution of the analysis target are compared to detect a section of the DNA sequence of the analysis target whose distribution does not match.

According to a second aspect of the present invention, there is provided the DN according to the first aspect.
In the A-sequence analysis method, the information processing device counts the number of base sequences in a section of a reference DNA sequence and a DNA sequence to be analyzed whose distributions do not match, and compares the results of the counting to insert and remove bases. It is characterized in that the missing is detected.

According to a third aspect of the present invention, there is provided the DN according to the first aspect.
In the A-sequence analysis method, the information processing device outputs at least a section of the DNA sequence to be analyzed whose distribution does not match as an analysis result.

According to a fourth aspect of the present invention, there are provided a storage means for storing a reference DNA sequence, an input means for inputting a DNA sequence to be analyzed, and a fixed number of base sequences for each of the reference DNA sequence and the DNA sequence to be analyzed. Sampling means for sequentially sampling at a base number interval smaller than a certain number; clustering means for clustering the sampled base sequence to obtain a distribution state in a Galaxy space; distribution of the reference sequence and distribution of the analysis target And means for detecting a section of the DNA sequence to be analyzed whose distribution does not match by comparing

[0009] The invention of claim 5 provides the above-described DN.
In the A-sequence analyzer, the number of base sequences in the section of the reference DNA sequence whose distribution does not match and the number of base sequences in the section of the DNA sequence to be analyzed are counted, and the results of the counting are compared to detect insertion and deletion of bases. It is characterized by further comprising means.

According to a sixth aspect of the present invention, there is provided the DN according to the fourth aspect.
The A-sequence analyzer further comprises means for outputting at least a section of the DNA sequence to be analyzed whose distribution does not match as an analysis result.

[0011]

Embodiments of the present invention will be described below in detail with reference to the drawings.

FIG. 1 is an explanatory diagram for explaining the processing procedure of the DNA sequence analysis method of the present embodiment. In this embodiment, when a DNA sequence is given, N (N
Is a positive number). The sampling sequence shifts the sampling position by M (M is a positive number smaller than N) in the sampling sequence. FIG. 1 shows an example in which M = 7 and N = 1. Since the combinations of the sampled base sequences are finite, similar combinations are combined into one set to create a plurality of sets. In this embodiment, creating a set is referred to as clustering. In the example of FIG. 1, since the sampled base sequences are different from each other, a set (called a word in this embodiment) W1, W2, W
3. . . Is created. In the present embodiment, a galaxy clustering method is used as a technique for clustering. This technique is based on the Hironobu Takah
ashi, Yoshitaka Nita, Taka
shi Endo, “Clustering Meth
od of large-scale Bigram
Network Specialization an
d Application to Text Ret
rieval “, Technical Report
of IECE, NLC-97-34, pp. 41-4
7, which will be briefly described because it relates to the present invention.

Assuming a virtual space (galaxy space) representing N-dimensional features, the position of one object in the galaxy space is represented by x. The order of a plurality of objects is represented by a number i. The similarity between the two objects at the positions xi and xj is represented by Mij. The distance between two object positions is represented by dij. A calculation formula for calculating the similarity and the distance is prepared in advance, and two objects among a plurality of objects are selected while differentiating the objects, and the similarity and the distance between the two objects are calculated.

When two objects are similar, the value of the similarity Mij is large and the distance di between the objects is di.
Since j also has the property of increasing, the similarity and distance 2
One set of parameters is used to create a plurality of sets of objects that are close to each other in the galaxy space.

If such a technique is used to characterize the position of a specific base or a combination of other adjacent bases, the word (sampled base sequence) can be clustered.

When clustered sets (words) are connected in order, they can be schematically displayed as shown in the lower part of FIG. In this display example, two-dimensional display is performed for illustration, but a plurality of sets are actually arranged in an N-dimensional space, that is, in a Galaxy space. In this embodiment, this arrangement, that is, the distribution state of words is treated as a feature of the DNA sequence.

Reference DN whose gene properties are known in advance
For the A-sequence, the above information processing is performed by an information processing device such as a personal computer, and the characteristics of the distribution of words (sets) in the Galaxy space are processed by the information processing device such as
Obtain by PC. Next, the above-described processing is also performed on the DNA sequence to be analyzed to acquire the characteristics of the distribution in the Galaxy space. FIGS. 2 to 4 schematically show two obtained distribution states. As shown in FIG. 2A, one base in the reference DNA sequence is the DN to be analyzed.
A sequence is an example of mutation to another base,
A word in the Galaxy space of the NA sequence is represented by D, and a word in the Galaxy space of the DNA sequence to be analyzed is represented by M. In FIG. 2 (B), the location of the mutated portion can be visually confirmed in the Galaxy space.
It can be seen that the state of distribution is different.

FIG. 3A shows a case where a base sequence not present in the reference DNA sequence is inserted into the DNA sequence to be analyzed, and FIG. 3B shows the arrangement of words in the Galaxy space in this case. Show. Here, the word to be analyzed is represented by I.

FIG. 4 shows a case where one or more base sequences in the reference DNA sequence are missing in the DNA sequence to be analyzed. FIG. 4B shows the distribution of words on the Galaxy space in this case. Here, the distribution of the analysis target is represented by V.

Therefore, in the present embodiment, the following can be understood by comparing the distribution states of two words in the Galaxy space. 1) The distance between two distributions is calculated, and a section where the calculated distance is larger than a predetermined threshold is a section different from the reference DNA sequence. Thereby, the section of the abnormal part can be detected by simple information processing. 2) Counting the number of words on the two distributions in the section in which the distance is greater than the threshold value, and comparing the counted numbers (calculating the difference), the type of mutation, insertion, or deletion can be determined. (A) If the number of words matches (the difference is 0), it is a mutation, and it is also found that there is a mutated part in the analysis target word having the largest distance. A mutated base sequence can also be detected by comparing the words of the DNA sequence in the abnormal section. (B) If the number of words in the reference DNA sequence is larger than the number of words to be analyzed, there is a missing in the DNA sequence to be analyzed, and the missing base sequence is also detected by comparing the bases of the DNA sequence in the abnormal section. be able to. (C) When the number of words in the reference DNA sequence is smaller than the number of words to be analyzed, a base sequence is inserted on the side of the DNA sequence to be analyzed, and the base inserted by comparison of the words in the DNA sequence in the abnormal section. Columns can also be detected.

A system for realizing the above-described DNA analysis method will now be described. Although the system can be realized by a general-purpose computer such as a personal computer or a digital circuit, an example in which the analysis function is realized by software of a general-purpose computer will be described.

FIG. 5 shows a functional configuration of a software program for realizing the analysis function. In FIG. 5, reference numeral 10 denotes a word extraction unit for sequentially sampling words from a DNA sequence to be analyzed given by input from a keyboard or a text file. Reference numeral 20 denotes a clustering unit that clusters the extracted words and outputs a word distribution on the Galaxy space.

Reference numeral 30 denotes a reference sequence storage unit which stores a reference (DNA) sequence given in the form of a text file or an input from a keyboard. A hard disk can be used as the reference sequence storage unit 30.

Reference numeral 40 denotes a word extracting unit for sequentially extracting words from the reference sequence, and the word extracting unit 10 can be commonly used. Reference numeral 50 denotes a clustering unit that clusters words in the reference sequence, and outputs a word distribution in the Galaxy space on the reference sequence side. The clustering units 20 and 40 can be shared.

Reference numeral 70 denotes a pattern analysis unit which analyzes the distribution of words output from the clustering units 20 and 50 by the above-described analysis method, and outputs the analysis result.
The output unit 70 is an output unit that outputs the analysis result output from the pattern analysis unit 60, and displays and outputs the analysis result in the form shown in FIG. 6, for example. As the output unit 70, a printer, a communication device, or the like can be used. Processing unit 1
The functions of 0, 20, 40, 50 and 60 are realized by the CPU executing the software program. The specific contents of the software program differ depending on the language form, and can be created by those skilled in the art based on the description of the analysis method described above.

The results of the analysis and analysis shown in FIG. 6 are displayed by comparing the base sequence of the reference DNA sequence with the DNA sequence to be analyzed, and the matching bases (sections in which the distance between words is equal to or less than the threshold value) are linearly matched. A base line portion that does not match (a portion where the word distribution is equal to or greater) is not drawn to indicate a base insertion portion or a missing portion. For the mutated portion, the user is notified by making the color of the base different from other displays. Also, a number indicating the order of each base in the DNA sequence is displayed.

In order to perform such display, the input DNA sequence to be analyzed is temporarily stored and displayed together with the DNA sequence stored in the hard disk. At this time, the order of bases is counted by a counter,
The counting result is displayed as a number indicating the base position. Bases connecting the straight lines are detected by the above-described analysis method. The above processing can be realized by executing software by the CPU.

The display form shown in FIG. 6 is one embodiment for explanation, and abnormal contents, its base sequence and word position may be output in the form of bases, and various other notification forms may be employed. be able to.

The following embodiment can be carried out in addition to the above embodiment. 1) In the above embodiment, the number of bases to be sampled is 7
The number of samples and the sampling interval are shown as one base, but the number of bases for sampling and the number of bases for sampling interval can be input from the keyboard etc. May be set. 2) A plurality of sets of reference DNA sequences may be prepared.
D to be analyzed from multiple sets of standard DNA sequences
A reference DNA-sequence similar to the NA sequence can also be detected. In this case, a distance calculation is performed for the word distribution, and the reference DN having the closest distance is used.
The A sequence is determined to be a similar DNA sequence. When identification information indicating the property of a gene is given to a plurality of reference DNA sequences and identification information of the detected similar reference DNA sequence is taken out, the type of the property of the gene of the DNA sequence to be analyzed is determined. Can be.

The reference D thus selected is
The analysis processing of the above embodiment may be performed on the NA sequence.

Although various modifications are possible in addition to the above-described embodiment, the modifications are within the technical scope of the present invention as long as the modifications are based on the technical idea described in the claims of the present application. Becomes

[0032]

According to the present invention as described above, when an experiment was actually performed, higher analysis accuracy was obtained as compared with the conventional analysis method. In the present invention, since the sampled base sequence is clustered, the base change in the base sequence change is captured as a characteristic of the DNA sequence.
Since this feature is woven into the Galaxy distribution,
It is considered that an inserted portion, a missing portion, or a mutated portion in a DNA sequence to be analyzed can be detected with higher accuracy.

[Brief description of the drawings]

FIG. 1 is an explanatory diagram for explaining a DNA analysis method according to an embodiment of the present invention.

FIG. 2 is an explanatory diagram for explaining analysis contents of the embodiment of the present invention.

FIG. 3 is an explanatory diagram for explaining analysis contents of the embodiment of the present invention.

FIG. 4 is an explanatory diagram for explaining analysis contents of the embodiment of the present invention.

FIG. 5 is a block diagram showing a functional configuration of a system according to the embodiment of the present invention.

FIG. 6 is an explanatory diagram showing a display example according to the embodiment of the present invention.

[Explanation of symbols]

 10, 40 word extraction unit 20, 50 clustering unit 60 pattern analysis unit 70 output unit

Continued on the front page (72) Inventor Ryuichi Oka 2-8-12 Higashi Kanda, Chiyoda-ku, Tokyo Ryukakusan Building 8F, Technology Research Association New Information Processing Development Machine Campus (72) Inventor Mori Yasuhide Higashi Koigakubo, Kokubunji-shi, Tokyo No. 280 F term in Hitachi Central Research Laboratory Co., Ltd. (reference) 4B024 AA11 CA01 HA11 HA19 4B029 AA07 AA23 BB20 FA10 4B063 QA01 QA12 QA13 QA18 QQ42 QS38 QS39

Claims (6)

[Claims] 1. A reference DNA sequence is stored in an information processing device, and a DNA sequence to be analyzed is given to the information processing device. The number of base sequences is sampled sequentially at a base number interval smaller than the certain number, and the sampled base sequences are clustered to obtain a distribution state in a Galaxy space, and the distribution of the reference sequence and the analysis target are obtained. A DNA sequence analysis method, comprising detecting a section of a DNA sequence to be analyzed whose distribution does not match by comparing with a distribution. 2. The DNA sequence analysis method according to claim 1, wherein the information processing device counts the number of base sequences in a section between the reference DNA sequence and the DNA sequence to be analyzed whose distributions do not match, and calculates the number of base sequences. A DNA sequence analysis method characterized by detecting insertion and deletion of a base by comparing the results. 3. The DNA sequence analysis method according to claim 1, wherein the information processing device outputs at least a section of the DNA sequence to be analyzed whose distribution does not match as an analysis result. . 4. A storage means for storing a reference DNA sequence; an input means for inputting a DNA sequence to be analyzed; and a base sequence having a fixed number of base sequences smaller than the fixed number for each of the reference DNA sequence and the DNA sequence to be analyzed. Sampling means for sequentially sampling at several intervals; clustering means for clustering the sampled base sequence to obtain a distribution state in the Galaxy space; and comparing the distribution of the reference sequence with the distribution of the analysis target. Means for detecting a section of the DNA sequence to be analyzed whose distribution does not match,
Sequence analyzer. 5. The DNA sequence analyzer according to claim 4, wherein the number of base sequences in the section of the reference DNA sequence whose distribution does not match and the number of base sequences in the section of the DNA sequence to be analyzed are counted, and the results of the counting are compared. A DNA sequence analyzer further comprising means for detecting insertion and deletion of a base. 6. The DNA sequence analyzer according to claim 4, further comprising means for outputting, as an analysis result, at least a section of the DNA sequence to be analyzed whose distribution does not match. .