Abstract
BackgroundThe Basic Local Alignment Search Tool (BLAST) is a fundamental program in the life sciences that searches databases for sequences that are most similar to a query sequence. Currently, the BLAST algorithm utilizes a query-indexed approach. Although many approaches suggest that sequence search with a database index can achieve much higher throughput (e.g., BLAT, SSAHA, and CAFE), they cannot deliver the same level of sensitivity as the query-indexed BLAST, i.e., NCBI BLAST, or they can only support nucleotide sequence search, e.g., MegaBLAST. Due to different challenges and characteristics between query indexing and database indexing, the existing techniques for query-indexed search cannot be used into database indexed search.ResultsmuBLASTP, a novel database-indexed BLAST for protein sequence search, delivers identical hits returned to NCBI BLAST. On Intel Haswell multicore CPUs, for a single query, the single-threaded muBLASTP achieves up to a 4.41-fold speedup for alignment stages, and up to a 1.75-fold end-to-end speedup over single-threaded NCBI BLAST. For a batch of queries, the multithreaded muBLASTP achieves up to a 5.7-fold speedups for alignment stages, and up to a 4.56-fold end-to-end speedup over multithreaded NCBI BLAST.ConclusionsWith a newly designed index structure for protein database and associated optimizations in BLASTP algorithm, we re-factored BLASTP algorithm for modern multicore processors that achieves much higher throughput with acceptable memory footprint for the database index.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-016-1302-4) contains supplementary material, which is available to authorized users.
Highlights
The Basic Local Alignment Search Tool (BLAST) is a fundamental program in the life sciences that searches databases for sequences that are most similar to a query sequence
National center for biotechnology information (NCBI) BLAST+ [2] uses pthreads to speed up BLAST on a multicore Central processing unit (CPU)
Database indexing that aligns a query to millions of database sequences instead of a single database sequence iteratively will suffer more from such irregularities, leading to serious performance degradation. To overcome these challenges of database indexing for protein sequence search, we propose muBLASTP, a novel BLASTP algorithm that includes an advanced index data structure for sequences of the database and a set of optimizations for the BLASTP algorithm
Summary
The Basic Local Alignment Search Tool (BLAST) is a fundamental program in the life sciences that searches databases for sequences that are most similar to a query sequence. The BLAST algorithm utilizes a query-indexed approach. Many approaches suggest that sequence search with a database index can achieve much higher throughput (e.g., BLAT, SSAHA, and CAFE), they cannot deliver the same level of sensitivity as the query-indexed BLAST, i.e., NCBI BLAST, or they can only support nucleotide sequence search, e.g., MegaBLAST. The Basic Local Alignment Search Tool (BLAST) [1] is a fundamental algorithm in life sciences that compares a query sequence to a database of sequences, i.e., subject sequences, to identify sequences that are the most similar to the query sequence. There are few recent studies that focus on improving the performance of CPU implementations of the widely-used BLAST algorithm
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