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PSAR: measuring multiple sequence alignment reliability by probabilistic sampling.

Jaebum Kim1, Jian Ma

  • 1Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA.

Nucleic Acids Research
|May 18, 2011
PubMed
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We developed a new alignment reliability score called probabilistic sampling-based alignment reliability (PSAR). This method directly assesses alignment quality by comparing it to suboptimal alignments, improving comparative genomics analyses.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Multiple sequence alignment is crucial for comparative genomics but is inherently difficult and prone to errors.
  • Assessing the reliability of sequence alignments is essential for accurate downstream analyses.

Purpose of the Study:

  • To introduce a novel method for quantifying the reliability of multiple sequence alignments.
  • To provide a more direct and robust measure of alignment quality compared to existing heuristic approaches.

Main Methods:

  • Developed a probabilistic sampling-based alignment reliability (PSAR) score.
  • Generated suboptimal alignments using pairwise comparisons between sequences and their respective sub-alignments.
  • Computed alignment reliability based on the agreement between the input alignment and generated suboptimal alignments.

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Main Results:

  • The PSAR score demonstrated superior performance over existing methods in simulation-based benchmarks.
  • Suboptimal alignments were found to be highly informative for assessing alignment reliability.
  • Applied PSAR to UCSC Genome Browser alignments, evaluating reliability across different genomic regions.

Conclusions:

  • The PSAR method offers a reliable and effective approach to measure multiple sequence alignment quality.
  • This method can guide cross-species conservation studies by identifying reliable alignments in various genomic regions.