Gene order fragment fast positioning method based on bitmap

Abstract

The invention discloses a gene order fragment fast positioning method based on a bitmap; the method comprises the following steps: constructing the bitmap, circulating and excursing each gene order fragment in a gene reference chain one by one so as to form a plurality of gene order fragment vectors, mapping the vectors to the only data bit in the bitmap, replacing 0 by 1, counting 1 appearing frequency t before the column on which the line located, and storing a key value in a t position of a Hash bucket corresponding to a line number R of the data bit in the database. If all data bits are set by 1, adding the data bits into a clash assembly; circulating and excursing to-be-positioned gene order fragments one by one so as to form a plurality of gene order fragment vectors, mapping the vectors to the only data bit in the bitmap, thus positioning a Hash data table. The positioning method can fast filter untargeted query data, can provide relatively accurate data positions of the Hash bucket, thus greatly accelerating a Hash bucket dividing mode organizing data query process; the gene order fragment fast positioning method based on the bitmap is high in space efficiency, fast in positioning speed, and accurate in positioning.

Description

technical field [0001] The invention relates to gene sequencing technology, in particular to a bitmap-based rapid positioning method for gene sequence fragments. Background technique [0002] Gene fragment mapping technology is the basis of current high-throughput gene sequencing. Through high-throughput sequencing, a large number of gene sequence fragments can be generated. Actual experiments have found that most of the gene sequence fragments can find accurate and complete matches in the longer reference gene sequence. The reference gene sequence can be regarded as a continuous string composed of A, C, G, T4 letters, and its length can usually be much more than 10 9 characters, starting from each character in such a long reference gene sequence, intercepting n characters as the Key in the Key-Value database, its position on the reference chain and other incidental information as Value, can be organized into a huge Key-Value database. [0003] Generally speaking, it is m...

AI Technical Summary

Problems solved by technology

In summary, the purpose of BloomFilter design is mainly for the situation that most of the query data does not hit the data in the database. Its disadvantage is that it can only give a simple "possible In" or "must not be" results, in the actual query process, if most of the data can hit the collection, then the calculation of BloomFilter may become a burden instead

Images