A computational method for genotype calling in family-based sequencing data

BMC Bioinformatics
Lun-Ching ChangWei Chen

Abstract

As sequencing technologies can help researchers detect common and rare variants across the human genome in many individuals, it is known that jointly calling genotypes across multiple individuals based on linkage disequilibrium (LD) can facilitate the analysis of low to modest coverage sequence data. However, genotype-calling methods for family-based sequence data, particularly for complex families beyond parent-offspring trios, are still lacking. In this study, first, we proposed an algorithm that considers both linkage disequilibrium (LD) patterns and familial transmission in nuclear and multi-generational families while retaining the computational efficiency. Second, we extended our method to incorporate external reference panels to analyze family-based sequence data with a small sample size. In simulation studies, we show that modeling multiple offspring can dramatically increase genotype calling accuracy and reduce phasing and Mendelian errors, especially at low to modest coverage. In addition, we show that using external panels can greatly facilitate genotype calling of sequencing data with a small number of individuals. We applied our method to a whole genome sequencing study of 1339 individuals at ~10X coverage from the...Continue Reading

References

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Citations

May 16, 2019·Journal of Translational Medicine·Laura Bravo-MerodioAnimesh Acharjee
Oct 18, 2020·Translational Stroke Research·Zsuzsanna AmentAnimesh Acharjee

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Methods Mentioned

BETA
genotyping
chips
chip

Software Mentioned

1000GP
TrioCaller
SHAPEIT
SAMtools
Genome Analysis Toolkit ( GATK )
Beagle
IMPUTE2
BWA
Genome Analysis Toolkit ( GATK
GATK

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