TY - JOUR
T1 - A New Fast Phasing Method Based On Haplotype Subtraction
AU - Mocci, Evelina
AU - Debeljak, Marija
AU - Klein, Alison P.
AU - Eshleman, James R.
N1 - Funding Information:
Supported in part by the Sol Goldman Pancreatic Cancer Research Center (J.R.E.), the STRINGER Foundation (J.R.E.), the Michael Rolfe Pancreatic Cancer Foundation (J.R.E.), the Mary Lou Wootton Pancreatic Cancer Research Fund (J.R.E.), and The Sidney Kimmel Comprehensive Cancer Center grant NCI P30CA006973 .
Publisher Copyright:
© 2019 American Society for Investigative Pathology and the Association for Molecular Pathology
PY - 2019/5
Y1 - 2019/5
N2 - We developed a novel phasing approach, based solely on molecules and genotype frequency, that does not rely on inference of new alleles. We initiated the project because of errors that were detected in the phased 1000 Genomes Project data. The algorithm first combined identical genotypes into clusters and ranked them by descending frequency. Using alleles defined in homozygotes, it combined them to produce expected genotypes that were dismissed and subtracted them from remaining genotypes to define additional new putative alleles. Putative alleles had to be confirmed by identifying them in independent genotypes, and the process was iterated until all alleles were identified. The new approach was validated using single-molecule sequencing of eight loci, 145 (8 to 35 per locus) alleles were identified, and an average 98.2% (range, 95.0% to 99.9%) of 1000 genome individuals at these loci were explained. The accuracy of the new method was compared with that from PHASE and SHAPEIT2 to the experimentally determined genotypes based on single-molecule sequencing. Our method was comparable to PHASE and SHAPEIT2 in accuracy but was, on average, 14.6- and 10.8-fold faster, respectively.
AB - We developed a novel phasing approach, based solely on molecules and genotype frequency, that does not rely on inference of new alleles. We initiated the project because of errors that were detected in the phased 1000 Genomes Project data. The algorithm first combined identical genotypes into clusters and ranked them by descending frequency. Using alleles defined in homozygotes, it combined them to produce expected genotypes that were dismissed and subtracted them from remaining genotypes to define additional new putative alleles. Putative alleles had to be confirmed by identifying them in independent genotypes, and the process was iterated until all alleles were identified. The new approach was validated using single-molecule sequencing of eight loci, 145 (8 to 35 per locus) alleles were identified, and an average 98.2% (range, 95.0% to 99.9%) of 1000 genome individuals at these loci were explained. The accuracy of the new method was compared with that from PHASE and SHAPEIT2 to the experimentally determined genotypes based on single-molecule sequencing. Our method was comparable to PHASE and SHAPEIT2 in accuracy but was, on average, 14.6- and 10.8-fold faster, respectively.
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U2 - 10.1016/j.jmoldx.2018.12.004
DO - 10.1016/j.jmoldx.2018.12.004
M3 - Article
C2 - 30872187
AN - SCOPUS:85064548663
SN - 1525-1578
VL - 21
SP - 427
EP - 436
JO - Journal of Molecular Diagnostics
JF - Journal of Molecular Diagnostics
IS - 3
ER -