inGAP: an integrated next-generation genome analysis pipeline

Item Type Journal Article
Author Ji Qi
Author Fangqing Zhao
Author Anne Buboltz
Author Stephan C Schuster
URL http://www.ncbi.nlm.nih.gov/pubmed/19880367
Volume 26
Issue 1
Pages 127-129
Publication Bioinformatics (Oxford, England)
ISSN 1367-4811
Date Jan 1, 2010
Extra PMID: 19880367
Journal Abbr Bioinformatics
DOI 10.1093/bioinformatics/btp615
Accessed 2009-12-30 14:23:52
Library Catalog NCBI PubMed
Abstract 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
Title inGAP: an integrated next-generation genome analysis pipeline
Short Title inGAP
Date Added 2009-12-30 09:23
Date Modified 2009-12-30 09:23