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 language | English |
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Pages (from-to) | 127-129 |
Number of pages | 3 |
Journal | Bioinformatics |
Volume | 26 |
Issue number | 1 |
DOIs | |
Publication status | Published - Oct 30 2009 |
Externally published | Yes |
ASJC Scopus Subject Areas
- Statistics and Probability
- Biochemistry
- Molecular Biology
- Computer Science Applications
- Computational Theory and Mathematics
- Computational Mathematics