DREAM-Stellar: parallel and space efficient exact local alignment
Evelin Aasna, Simon Gene Gottlieb, Marcel Ehrhardt, Knut Reinert
TL;DR
DREAM-Stellar is a fast and efficient tool for finding local alignments in genomic sequences using parallel computing and improved filtering techniques.
Contribution
DREAM-Stellar introduces a parallelized and space-efficient local aligner with a new prefilter and IBF data structure for improved performance on genomic data.
Findings
DREAM-Stellar is up to 900 times faster on 32 threads than its single-threaded predecessor.
The tool can find all alignments between a pair of genomes in minutes.
Heuristic tools like BLAST miss or overwhelm significant local alignments with less significant matches.
Abstract
Searching large genomic data sets for local alignments poses a computational challenge. A particular obstacle is the handling of repetitive sequences that appear in various contexts and incur a high runtime cost. For practical homology search, it is important to develop a specific but sensitive filter. Good filters reduce the search space before alignment without missing significant matches. We introduce DREAM-Stellar, a parallelized, updated version of the pairwise local aligner Stellar. The new aligner, DREAM-Stellar, is composed of four steps: preprocessing the queries and references, building a data structure for distributing the queries, computing in parallel the results and finally combining them. For distributing the queries we use the IBF data structure and a new prefilter for local alignments. We present our comparison of five local aligners on simulated and real genomic data…
Genes, proteins, chemicals, diseases, species, mutations and cell lines named across the full text — each resolved to its canonical identifier and authoritative record.
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Taxonomy
TopicsGenomics and Phylogenetic Studies · Genome Rearrangement Algorithms · Algorithms and Data Compression