inGAP: an integrated next-generation genome analysis pipeline.
CONCLUSIONS
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.


BACKGROUND
inGAP is available at http://sites.google.com/site/nextgengenomics/ingap
Qi
Ji
J
Pennsylvania State University, Center for Comparative Genomics and Bioinformatics, University Park, Pennsylvania 16802, USA.
Zhao
Fangqing
F
Buboltz
Anne
A
Schuster
Stephan C
SC
D000465:Algorithms; D001483:Base Sequence; D002874:Chromosome Mapping / Q000379:methods*; D004252:DNA Mutational Analysis / Q000379:methods*; D016678:Genome / Q000235:genetics*; D008969:Molecular Sequence Data; D000073718:Pancreatitis-Associated Proteins; D020641:Polymorphism, Single Nucleotide / Q000235:genetics*; D017422:Sequence Analysis, DNA / Q000379:methods*; D012984:Software; D018511:Systems Integration; D014584:User-Computer Interface