NDLI: Parallel Pair-HMM SNP Detection

Content Provider	IEEE Xplore Digital Library
Author	Clement, N.L. Shepherd, B.A. Bodily, P. Tumur-Ochir, S. Younghoon Gim Snell, Q. Clement, M.J. Johnson, W.E.
Copyright Year	2012
Abstract	I. MOTIVATION: Due to the massive amounts of data generated from each instrument run, next generation sequencing technologies have presented researchers with unique analytical challenges which require innovative, computationally efficient statistical solutions. Here we present a parallel implementation of a probabilistic Pair-Hidden Markov Model for base calling and SNP detection in next generation sequencing data. Our approach incorporates multiple sources of error into the base calling procedure which leads to more accurate results. In addition, our approach applies a likelihood ratio test that provides researchers with straight-forward SNP calling cutoffs based on a p-value cutoff or a false discovery control. II. RESULTS: We have developed GNUMAP-SNP, which is a highly accurate approach for the identification of SNPs in next generation sequencing data. By utilizing a novel probabilistic Pair-Hidden Markov Model, GNUMAP-SNP effectively accounts for uncertainty in the read calls as well as read mapping in an unbiased fashion. Our results show that GNUMAP-SNP has both high sensitivity and high specificity throughout the genome, which is especially true in repeat regions or in areas with low read coverage. In addition, we propose a statistical framework that accounts for the background noise using straightforward statistical cutoffs which filters out false-positive results. The parallel implementation of SNP calling achieves near linear speedup on distributed memory or shared memory platforms. III. AVAILABILITY: GNUMAP-SNP is available as a module in the GNUMAP probabilistic read mapping software. GNUMAP is freely available for download at: http://dna.cs.byu.edu/gnumap/.
Starting Page	675
Ending Page	683
File Size	577590
Page Count	9
File Format	PDF
ISBN	9781467309745
DOI	10.1109/IPDPSW.2012.84
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-05-21
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Frequency modulation Parallel computing Next-generation sequencing Short-read mapping Sequence mappers Genomics Markov processes Probability Biology computing Probabilistic logic Bioinformatics Next generation networking
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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