Journal Article

inGAP: an integrated next-generation genome analysis pipeline

Ji Qi, Fangqing Zhao, Anne Buboltz and Stephan C. Schuster

in Bioinformatics

Volume 26, issue 1, pages 127-129
Published in print January 2010 | ISSN: 1367-4803
Published online October 2009 | e-ISSN: 1460-2059 | DOI: http://dx.doi.org/10.1093/bioinformatics/btp615

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Summary: We develop a novel mining pipeline, Integrative Next-generation Genome Analysis 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@bx.psu.edu

Supplementary information: Supplementary data are available at Bioinformatics online.

Journal Article.  1517 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology

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