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. © The Author(s) 2009. Published by Oxford University Press.
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CITATION STYLE
Qi, J., Zhao, F., Buboltz, A., & Schuster, S. C. (2009). inGAP: An integrated next-generation genome analysis pipeline. Bioinformatics, 26(1), 127–129. https://doi.org/10.1093/bioinformatics/btp615
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