Estimation of intrafamilial DNA contamination in family trio genome sequencing using deviation from Mendelian inheritance

Christopher J. Yoon, Su Yeon Kim, Chang Hyun Nam, Junehawk Lee, Jung Woo Park, Jihyeob Mun, Seongyeol Park, Soyoung Lee, Boram Yi, Kyoung Il Min, Brian Wiley, Kelly L. Bolton, Jeong Ho Lee, Eunjoon Kim, Hee Jeong Yoo, Jong Kwan Jun, Ji Seon Choi, Malachi Griffith, Obi L. Griffith, Young Seok Ju

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

With the increasing number of sequencing projects involving families, quality control tools optimized for family genome sequencing are needed. However, accurately quantifying contamination in a DNA mixture is particularly difficult when genetically related family members are the sources. We developed TrioMix, a maximum likelihood estimation (MLE) framework based on Mendel’s law of inheritance, to quantify DNA mixture between family members in genome sequencing data of parent–offspring trios. TrioMix can accurately deconvolute any intrafamilial DNA contamination, including parent–offspring, sibling–sibling, parent–parent, and even multiple familial sources. In addition, TrioMix can be applied to detect genomic abnormalities that deviate from Mendelian inheritance patterns, such as uniparental disomy (UPD) and chimerism. A genome-wide depth and variant allele frequency plot generated by TrioMix facilitates tracing the origin of Mendelian inheritance deviations. We showed that TrioMix could accurately deconvolute genomes in both simulated and real data sets.

Original languageEnglish
Pages (from-to)2134-2144
Number of pages11
JournalGenome research
Volume32
Issue number11-12
DOIs
StatePublished - Nov 2022

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