Compressed indexing and local alignment of DNA
Author(s) -
TakWah Lam,
WingKin Sung,
Siu-Lung Tam,
Ching Wong,
SM Yiu
Publication year - 2008
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btn032
Subject(s) - substring , search engine indexing , computer science , genome , smith–waterman algorithm , dynamic programming , byte , index (typography) , human genome , software , pattern matching , matching (statistics) , heuristic , theoretical computer science , string searching algorithm , algorithm , data structure , artificial intelligence , sequence alignment , biology , mathematics , genetics , gene , statistics , world wide web , peptide sequence , programming language , operating system
Recent experimental studies on compressed indexes (BWT, CSA, FM-index) have confirmed their practicality for indexing very long strings such as the human genome in the main memory. For example, a BWT index for the human genome (with about 3 billion characters) occupies just around 1 G bytes. However, these indexes are designed for exact pattern matching, which is too stringent for biological applications. The demand is often on finding local alignments (pairs of similar substrings with gaps allowed). Without indexing, one can use dynamic programming to find all the local alignments between a text T and a pattern P in O(|T||P|) time, but this would be too slow when the text is of genome scale (e.g. aligning a gene with the human genome would take tens to hundreds of hours). In practice, biologists use heuristic-based software such as BLAST, which is very efficient but does not guarantee to find all local alignments.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom