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Supplementary Note In Wasik Et Al. 2021.pdf

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Preview of Supplementary Note in Wasik et al. 2021
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Summary

This note describes the imputation algorithm for low-pass sequencing data in loimpute v0.18, based on the copying model by Li and Stephens (2003). It models the transition probabilities between haplotypes and emission probabilities of sequencing reads given a genotype, using a hidden Markov model. The algorithm estimates the posterior probability of each genotype in a target individual, with a time complexity of O(NM2), which is mitigated by selecting a small set of plausible haplotypes to run the full algorithm, choosing the top 100 haplotypes that share rare variants with the target individual.

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Description

This note describes the imputation algorithm for low-pass sequencing data in loimpute v0.18, based on the copying model by Li and Stephens (2003).

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  • File Format: PDF
  • File Size: 121 KB
  • Pages: 3
  • Language: EN
  • Total Downloads: 169
  • Last Updated: 2 days ago

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