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STELLAR: fast and exact local alignments.

Birte Kehr1, David Weese, Knut Reinert

  • 1Department of Computer Science, Free University Berlin, Takustr. 9, 14195 Berlin, Germany. birte.kehr@fu-berlin.de

BMC Bioinformatics
|December 14, 2011
PubMed
Summary
This summary is machine-generated.

STELLAR is a novel local alignment tool that guarantees full sensitivity for genomic sequence comparisons. It accurately identifies significant local alignments missed by heuristic tools like BLAST, improving genomic data analysis.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Accurate local alignment search is crucial for large-scale genomic sequence comparison.
  • Existing heuristic tools, such as BLAST and BLAT, may miss significant matches due to their speed-oriented algorithms.

Purpose of the Study:

  • To introduce STELLAR, a novel local pairwise aligner with full sensitivity for ε-alignments.
  • To demonstrate STELLAR's capability in identifying all local alignments within specified error tolerances.

Main Methods:

  • STELLAR employs a two-step approach: lossless filtering using the SWIFT algorithm and an exact verification strategy.
  • The verification strategy was rigorously proven to be exact.

Main Results:

  • STELLAR achieves full sensitivity for ε-alignments, reporting all matches meeting length and error rate criteria.
  • Simulated and real genomic data analyses confirmed that heuristic tools miss a substantial percentage of significant local alignments.
  • STELLAR demonstrated high performance and speed on very long sequences.

Conclusions:

  • STELLAR is a practical and fast tool for finding local alignments in genomic sequences using the edit distance model.
  • It offers a significant improvement over heuristic methods for sensitive local alignment detection.
  • STELLAR is freely available for multiple operating systems, with source code integrated into the SeqAn C++ library.