iBLAST: Incremental BLAST of new sequences via automated e-value correction

Area of Science:

• Bioinformatics
• Computational Biology
• Genomics

Background:

• Genomic databases are rapidly expanding, affecting the accuracy of sequence similarity search results.
• Traditional BLAST searches require rerunning against the entire updated database, wasting computational resources.

Purpose of the Study:

• To introduce iBLAST, a novel method for efficiently updating previous BLAST search results.
• To reduce the computational cost and time associated with re-analyzing large, growing genomic datasets.

Main Methods:

• iBLAST leverages existing BLAST results to query only the incremental portion of a growing database.
• It recomputes relevant statistics, such as expect values (e-values), and integrates them into updated results.

Main Results:

• iBLAST produces identical results to NCBI BLAST searches.
• The method offers substantial computational savings, performing (1 + δ)/δ times faster than NCBI BLAST, where δ is the database growth fraction.

Conclusions:

• iBLAST provides a highly efficient and cost-effective solution for updating genomic database searches.
• This approach enables faster biological discovery with reduced computational overhead.