| Title: | A novel method for across-chromosome phasing without relative data |
| Journal: | Bioinformatics |
| Published: | 3 May 2026 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/42128011/ |
| DOI: | https://doi.org/10.1093/bioinformatics/btag277 |
Publication 20184
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Abstract
MOTIVATION: Across-chromosome phasing identifies which haplotypes of different chromosomes come from the same parent. This differs from within-chromosome phasing, which uses linkage disequilibrium patterns to determine which alleles were co-inherited within each chromosome but does not match haplotypes across different chromosomes. While across-chromosome phasing can be conducted using genotypes from parents or close relatives, current methods perform poorly for samples of unrelated individuals. Here, we introduce a novel approach for across-chromosome phasing that employs a window-based SNP-similarity metric, eliminating the need for data from close relatives or detection of identical-by-descent haplotypes.</p>
RESULTS: Using UK Biobank offspring with both parents genotyped as a gold standard, we evaluated the performance of our method by phasing the offspring without using parental data. In genomic data with no within-chromosome phase errors, our algorithm achieved a mean across-chromosome phasing accuracy of 95%, with 53% of individuals phased perfectly. When data was pre-phased computationally using a standard within-chromosome phasing algorithm, mean accuracy for across-chromosome phasing dropped to 83.1%. Thus, our method is limited primarily by the accuracy of within-chromosome phasing accuracy and can approach near-perfect across-chromosome phasing accuracy as within-chromosome phasing accuracy improves.</p>
AVAILABILITY AND IMPLEMENTATION: The implementation was executed within a multi-node computational environment of University of Colorado Boulder Research Computing (Blanca Cluster: https://www.colorado.edu/rc/resources/blanca), employing parallelization techniques in the C programming language. The source code has been made publicly accessible online at https://github.com/emmanuelsapin/AcrossChromosomesPhasing, thereby facilitating reproducibility of the results for researchers with authorized access to the UK Biobank dataset.</p>
8 Keywords
- Algorithms
- Chromosomes
- Genomics
- Genotype
- Haplotypes
- Humans
- Linkage Disequilibrium
- Polymorphism, Single Nucleotide
3 Authors
- Emmanuel Sapin
- Kristen M Kelly
- Matthew C Keller
1 Application
| Application ID | Title |
|---|---|
| 16651 | Genetic architecture of disease and related anthropometric phenotypes |
Enabling scientific discoveries that improve human health