Calling known variants and identifying new variants while rapidly aligning sequence data

P. M. VanRaden,1 D.M. Bickhart,1 and J.R. O'Connell2

1Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD 20705-2350
2University of Maryland School of Medicine, Baltimore, MD 21201


2018 J. Dairy Sci (?)
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ABSTRACT

Whole-genome sequencing studies can identify causative mutations for subsequent use in genomic evaluations. Speed and accuracy of sequence data processing can be improved by calling known variant alleles during alignment instead of the separate alignment and calling steps in previous programs. Alignment using Burrows–Wheeler Alignment (BWA) or SNAP and variant identification using Genome Analysis ToolKit (GATK) or SAMtools were compared to new programs Findmap and Findvar. Findmap stores both the reference map and known alternate alleles in a hash table to simultaneously align reads and count reference and alternate alleles for each DNA source. Potential new single nucleotide variant, insertion, and deletion alleles are output for summary by variant identification program Findvar. Strategies were tested using cattle, human, and a completely random reference map and simulated or actual data. Most tests simulated 10 bulls each with 10× simulated sequence reads containing 39 million variants from the 1000 Bull Genomes Project. With 10 processors, clock times to process 100× data were 105 h for BWA, 25 h for GATK, and 11 h for SAMtools but only about 4 h for SNAP, 3 h for Findmap, and 1 h for Findvar. Alignment programs required about the same total memory; BWA used 46 GB (4.6 GB/processor), whereas >10 processors can share the same memory in SNAP and Findmap, which used 40 and 46 GB, respectively. Findmap correctly mapped 92.9% of reads (compared with 92.6% from SNAP and 90.5% from BWA) and had high accuracy of calling alleles for known variants. For new variants, Findvar found 99.8% of single nucleotide variants, 79% of insertions, and 67% of deletions; GATK found 99.4, 95, and 90%; and SAMtools found 99.8, 12, and 16%, respectively. False positives (as percentages of true variants) were 11% of single nucleotide variants, 0.4% of insertions, and 0.3% of deletions from Findvar; 12, 8.4, and 2.9% from GATK; and 37, 1.3, and 0.4% from SAMtools, respectively. Advantages of Findmap and Findvar are fast processing, precise alignment, more useful data summaries, more compact output, and fewer steps. Calling known and identifying new variants during alignment allows more efficient and accurate sequence-based genotyping.