| Title: | Genotype error biases trio-based estimates of haplotype phase accuracy |
| Journal: | American Journal of Human Genetics |
| Published: | 1 Jun 2022 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/35659928/ |
| DOI: | https://doi.org/10.1016/j.ajhg.2022.04.019 |
| URL: | http://www.cell.com/article/S0002929722002063/pdf |
| Citations: | 9 (6 in last 2 years) as of 8 Aug 2024 |
Publication 12353
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Abstract
Haplotypes can be estimated from unphased genotype data via statistical methods. When parent-offspring trios are available for inferring the true phase from Mendelian inheritance rules, the accuracy of statistical phasing is usually measured by the switch error rate, which is the proportion of pairs of consecutive heterozygotes that are incorrectly phased. We present a method for estimating the genotype error rate from parent-offspring trios and a method for estimating the bias that occurs in the observed switch error rate as a result of genotype error. We apply these methods to 485,301 genotyped UK Biobank samples that include 898 White British trios and to 38,387 sequenced TOPMed samples that include 217 African Caribbean trios and 669 European American trios. We show that genotype error inflates the observed switch error rate and that the relative bias increases with sample size. For the UK Biobank White British trios, the observed switch error rate in the trio offspring is 2.4 times larger than the estimated true switch error rate (1.4 × 10-3 vs 5.8 × 10-4. We propose an alternate definition of phase error that counts two consecutive switch errors as a single error because back-to-back switch errors arise when a single heterozygote is incorrectly phased with respect to the surrounding heterozygotes. With this definition, we estimate that the average distance between phase errors is 64 megabases in the UK Biobank White British individuals.</p>
6 Keywords
- Bias
- Genotype
- Haplotypes
- Heredity
- Humans
- Polymorphism, Single Nucleotide
2 Authors
- Brian L Browning
- Sharon R Browning
1 Application
| Application ID | Title |
|---|---|
| 19934 | Statistical and Computational Genetics Methods Development |
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