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Grigora SNP s: Optimized Analysis of SNP s for DNA Forensics ,
Author(s) -
Ricke Darrell O.,
Shcherbina Anna,
Michaleas Adam,
FremontSmith Philip
Publication year - 2018
Publication title -
journal of forensic sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.715
H-Index - 96
eISSN - 1556-4029
pISSN - 0022-1198
DOI - 10.1111/1556-4029.13794
Subject(s) - snp , bottleneck , computational biology , single nucleotide polymorphism , computer science , genetics , snp array , biology , genotype , gene , embedded system
High‐throughput sequencing ( HTS ) of single nucleotide polymorphisms ( SNP s) enables additional DNA forensic capabilities not attainable using traditional STR panels. However, the inclusion of sets of loci selected for mixture analysis, extended kinship, phenotype, biogeographic ancestry prediction, etc., can result in large panel sizes that are difficult to analyze in a rapid fashion. Grigora SNP was developed to address the allele‐calling bottleneck that was encountered when analyzing SNP panels with more than 5000 loci using HTS . Grigora SNP s uses a MapReduce parallel data processing on multiple computational threads plus a novel locus‐identification hashing strategy leveraging target sequence tags. This tool optimizes the SNP calling module of the DNA analysis pipeline with runtimes that scale linearly with the number of HTS reads. Results are compared with SNP analysis pipelines implemented with SAM tools and GATK . Grigora SNP s removes a computational bottleneck for processing forensic samples with large HTS SNP panels.