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Published on: August 16, 2017
Indelign: a probabilistic framework for annotation of insertions and deletions in a multiple alignment
1Department of Computer Science, University of Illinois, Urbana-Champaign, Urbana, IL, USA.
Bioinformatics (Oxford, England)
|November 18, 2006
Summary
Indelign is a new program for analyzing molecular evolutionary events like insertions and deletions. It offers improved performance over existing methods and reveals an excess of insertions in Drosophila regulatory sequences.
Area of Science:
- Computational Biology
- Molecular Evolution
Background:
- Accurate multiple sequence alignment is crucial for studying molecular evolution.
- Annotating insertions and deletions (indels) in genomic data remains a challenge, particularly within a probabilistic framework.
Purpose of the Study:
- To introduce Indelign, a novel program for probabilistic modeling of indel events.
- To improve the accuracy of indel annotation and multiple sequence alignment.
Main Methods:
- Indelign employs a probabilistic evolutionary model to infer indel scenarios from multiple sequence alignments.
- The program can refine alignments to better fit the evolutionary model.
Main Results:
- Indelign demonstrates near-optimal performance and significant improvements over alternative methods on synthetic data.
- Analysis of Drosophila regulatory sequences using Indelign shows a higher rate of insertions than deletions.
Conclusions:
- Indelign provides a robust probabilistic framework for analyzing indel events in molecular evolution.
- The findings suggest distinct evolutionary pressures on regulatory sequences compared to neutral sequences.
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