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Bioinformatics Advance Access published online on October 30, 2009
Bioinformatics, doi:10.1093/bioinformatics/btp615
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© 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.

inGAP: an integrated next-generation genome analysis pipeline

Ji Qi {dagger}, Fangqing Zhao {dagger}, Anne Buboltz and Stephan C. Schuster *

Pennsylvania State University, Center for Comparative Genomics and Bioinformatics, University Park, Pennsylvania 16802, USA.

*To whom correspondence should be addressed. Stephan C. Schuster, E-mail: scs{at}bx.psu.edu


  Abstract

Summary: We develop a novel mining pipeline, inGAP, guided by a Bayesian principle to detect single nucleotide polymorphisms (SNPs), insertion/deletions (indels) by comparing high-throughput pyrosequencing reads with a reference genome of related organisms. inGAP can be applied to the mapping of both Roche/454 and Illumina reads with no restriction of read length. Experiments on simulated and experimental data show that this pipeline can achieve overall 97% accuracy in SNP detection and 94% in the finding of indels. All the detected SNPs/indels can be further evaluated by a graphical editor in our pipeline. inGAP also provides functions of multiple genomes comparison and assistance of bacterial genome assembly.

Availability: inGAP is available at http://sites.google.com/site/nextgengenomics/ingap

Contact: scs{at}bx.psu.edu

Supplementary information: Supplementary data are available at Bioinformatics online.

Associate Editor: Dr. Alex Bateman

{dagger}The first two authors contributes equally to this work

Received on July 10, 2009; revised on October 20, 2009; accepted on October 23, 2009

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