inGAP: An integrated next-generation genome analysis pipeline

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

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

54 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)127-129
Number of pages3
JournalBioinformatics
Volume26
Issue number1
DOIs
Publication statusPublished - Oct 30 2009
Externally publishedYes

ASJC Scopus Subject Areas

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

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