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          Institute: MPI für molekulare Genetik     Collection: Department of Computational Molecular Biology     Display Documents



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ID: 451276.0, MPI für molekulare Genetik / Department of Computational Molecular Biology
Pindel: a pattern growth approach to detect break points of large deletions and medium sized insertions from paired-end short reads.
Authors:Ye, Kai; Schulz, Marcel H.; Long, Quan; Apweiler, Rolf; Ning, Zemin
Language:English
Date of Publication (YYYY-MM-DD):2009-06-26
Title of Journal:Bioinformatics
Journal Abbrev.:Bioinformatics
Volume:25
Issue / Number:21
Start Page:2865
End Page:2871
Full name of Issue-Editor(s):Valencia, Alfonso
Copyright:The Author(s) 2009. Published by Oxford University Press.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.5/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Review Status:not specified
Audience:Experts Only
Abstract / Description:Motivation:
There is a strong demand in the genomic community to develop effective algorithms to reliably identify genomic variants. Indel detection using next-gen data is difficult and identification of long structural variations is extremely challenging.
Results:
We present Pindel, a pattern growth approach, to detect breakpoints of large deletions and medium-sized insertions from paired-end short reads. We use both simulated reads and real data to demonstrate the efficiency of the computer program and accuracy of the results.
Comment of the Author/Creator:To whom correspondence should be addressed. Kai Ye
Contact: k.ye@lumc.nl; zn1@sanger.ac.uk

Availability: The binary code and a short user manual can be freely downloaded from http://www.ebi.ac.uk/~kye/pindel/.
External Publication Status:published
Document Type:Article
Communicated by:Martin Vingron
Affiliations:MPI für molekulare Genetik
External Affiliations:1.EMBL Outstation European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK;
2.Departments of Molecular Epidemiology, Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, The Netherlands;
3.The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK.
Identifiers:URL:http://bioinformatics.oxfordjournals.org/cgi/repri...
DOI:10.1093/bioinformatics/btp394
ISSN:1367-4803
Full Text:
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