| Title: | Novel Approach for Parallelizing Pairwise Comparison Problems as Applied to Detecting Segments Identical By Decent in Whole-Genome Data |
| Journal: | Bioinformatics |
| Published: | 11 Mar 2021 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/33705528/ |
| DOI: | https://doi.org/10.1093/bioinformatics/btab084 |
| URL: | https://academic.oup.com/bioinformatics/article-pdf/37/15/2121/39622380/btab084.pdf |
Publication 5476
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Abstract
MOTIVATION: Pairwise comparison problems arise in many areas of science. In genomics, datasets are already large and getting larger, and so operations that require pairwise comparisons-either on pairs of SNPs or pairs of individuals-are extremely computationally challenging. We propose a generic algorithm for addressing pairwise comparison problems that breaks a large problem (of order n2 comparisons) into multiple smaller ones (each of order n comparisons), allowing for massive parallelization.RESULTS: We demonstrated that this approach is very efficient for calling identical by descent (IBD) segments between all pairs of individuals in the UK Biobank dataset, with a 250-fold savings in time and 750-fold savings in memory over the standard approach to detecting such segments across the full dataset. This efficiency should extend to other methods of IBD calling and, more generally, to other pairwise comparison tasks in genomics or other areas of science.
2 Authors
- Emmanuel Sapin
- Matthew C Keller
Enabling scientific discoveries that improve human health