Format

Send to:

Choose Destination
See comment in PubMed Commons below
Bioinformatics. 2007 Jul 15;23(14):1851-3. Epub 2007 May 22.

Recombination-filtered genomic datasets by information maximization.

Author information

  • 1Arizona Research Laboratories-Biotechnology, University of Arizona, Tucson, AZ 85721, USA.

Abstract

With the increasing amount of DNA sequence data available from natural populations, new computational methods are needed to efficiently process raw sequences into formats that are applicable to a variety of analytical methods. One highly successful approach to inferring aspects of demographic history is grounded in coalescent theory. Many of these methods restrict themselves to perfectly tree-like genealogies (i.e. regions with no observed recombination), because theoretical difficulties prevent ready statistical evaluation of recombining regions. However, determining which recombination-filtered dataset to analyze from a larger recombination-rich genomic region is a non-trivial problem. Current applications primarily aim to quantify recombination rates (rather than produce optimal recombination-filtered blocks), require significant manual intervention, and are impractical for multiple genomic datasets in high-throughput, automated research environments. Here, we present a fast, simple and automatable command-line program that extracts optimal recombination-filtered blocks (no four-gamete violations) from recombination-rich genomic re-sequence data.

AVAILABILITY:

http://hammerlab.biosci.arizona.edu/software.html.

PMID:
17519249
[PubMed - indexed for MEDLINE]
Free full text
PubMed Commons home

PubMed Commons

0 comments
How to join PubMed Commons

    Supplemental Content

    Full text links

    Icon for HighWire
    Loading ...
    Write to the Help Desk