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SpartaABC: a web server to simulate sequences with indel parameters inferred using an approximate Bayesian

Haim Ashkenazy1, Eli Levy Karin1,2, Zach Mertens3

  • 1Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 69978, Israel.

Nucleic Acids Research
|May 2, 2017
PubMed
Summary
This summary is machine-generated.

SpartaABC infers insertion and deletion (indel) parameters from sequence data, enabling more accurate biological simulations. This tool helps researchers select appropriate indel parameters for sequence analysis and simulation studies.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Evolutionary Genetics

Background:

  • Multiple sequence alignments are crucial for biological analyses.
  • Parametric bootstrap procedures using sequence simulators are common for studying alignment results.
  • A key challenge is selecting appropriate insertion and deletion (indel) parameters for simulations to accurately reflect biological data.

Purpose of the Study:

  • To present SpartaABC, a novel web server designed to infer indel parameters from sequence data.
  • To provide users with a method for choosing indel parameters that generate biologically realistic sequences.
  • To facilitate more accurate sequence simulation studies.

Main Methods:

  • SpartaABC employs an approximate Bayesian computation (ABC) rejection algorithm.
  • The server extracts summary statistics from input sequence data.
  • It performs numerous sequence simulations with randomly sampled indel parameters and retains those yielding statistics close to the input data.

Main Results:

  • SpartaABC provides point estimates and approximate posterior distributions for indel parameters.
  • The server integrates Dawg 2.0 and INDELible for sequence simulation with inferred parameters.
  • Differences in indel dynamics were demonstrated across three protein-coding genes in mammalian orthologs.

Conclusions:

  • SpartaABC addresses the critical need for selecting appropriate indel parameters in sequence simulation.
  • The tool enhances the reliability of phylogenetic and evolutionary analyses.
  • It offers a valuable resource for researchers in bioinformatics and evolutionary biology.