RVD2: an ultra-sensitive variant detection model for low-depth heterogeneous next-generation sequencing data.
BACKGROUND
Next-generation sequencing technology is increasingly being used for clinical diagnostic tests. Clinical samples are often genomically heterogeneous due to low sample purity or the presence of genetic subpopulations. Therefore, a variant calling algorithm for calling low-frequency polymorphisms in heterogeneous samples is needed.


RESULTS
We present a novel variant calling algorithm that uses a hierarchical Bayesian model to estimate allele frequency and call variants in heterogeneous samples. We show that our algorithm improves upon current classifiers and has higher sensitivity and specificity over a wide range of median read depth and minor allele fraction. We apply our model and identify 15 mutated loci in the PAXP1 gene in a matched clinical breast ductal carcinoma tumor sample; two of which are likely loss-of-heterozygosity events.


METHODS
http://genomics.wpi.edu/rvd2/.


BACKGROUND
pjflaherty@wpi.edu


BACKGROUND
Supplementary data are available at Bioinformatics online.
Department of Biomedical Engineering, Worcester Polytechnic Institute, Worcester and.
Yuting
Y
He
Department of Biomedical Engineering, Worcester Polytechnic Institute, Worcester and.
Fan
F
Zhang
Department of Biomedical Engineering, Worcester Polytechnic Institute, Worcester and Department of Mathematics and Statistics, University of Massachusetts, Amherst, MA, USA.
Patrick
P
Flaherty
D000328:Adult; D000465:Algorithms; D000483:Alleles; D001499:Bayes Theorem; D014408:Biomarkers, Tumor / Q000235:genetics*; D001943:Breast Neoplasms / Q000235:genetics; D018270:Carcinoma, Ductal, Breast / Q000235:genetics; D005260:Female; D005787:Gene Frequency; D023281:Genomics; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods*; D006801:Humans; D019656:Loss of Heterozygosity; D009154:Mutation / Q000235:genetics*; D020641:Polymorphism, Single Nucleotide / Q000235:genetics*; D016415:Sequence Alignment; D017422:Sequence Analysis, DNA / Q000379:methods*; D012984:Software
D014408:Biomarkers, Tumor