TY  - JOUR
A1  - Yoon, Christopher J.
A1  - Kim, Su Yeon
A1  - Nam, Chang Hyun
A1  - Lee, Junehawk
A1  - Park, Jung Woo
A1  - Mun, Jihyeob
A1  - Park, Seongyeol
A1  - Lee, Soyoung
A1  - Yi, Boram
A1  - Min, Kyoung Il
A1  - Wiley, Brian
A1  - Bolton, Kelly L.
A1  - Lee, Jeong Ho
A1  - Kim, Eunjoon
A1  - Yoo, Hee Jeong
A1  - Jun, Jong Kwan
A1  - Choi, Ji Seon
A1  - Griffith, Malachi
A1  - Griffith, Obi L.
A1  - Ju, Young Seok
T1  - Estimation of intrafamilial DNA contamination in family trio genome sequencing using deviation from Mendelian inheritance
Y1  - 2022/11/01 
JF  - Genome Research 
JO  - Genome Research 
SP  - 2134 
EP  - 2144 
DO  - 10.1101/gr.276794.122 
VL  - 32 
IS  - 11-12 
UR  - http://genome.cshlp.org/content/32/11-12/2134.abstract 
N2  - 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. 
ER  -