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

Lun Ching Chang, Bingshan Li, Zhou Fang, Scott Vrieze, Matt McGue, William G. Iacono, George C. Tseng, Wei Chen

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


Background: 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. Results: 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 Minnesota Center for Twin and Family Research. Conclusions: The aggregated results show that our methods significantly outperform existing ones that ignore family constraints or LD information. We anticipate that our method will be useful for many ongoing family-based sequencing projects. We have implemented our methods efficiently in a C++ program FamLDCaller, which is available from http://www.pitt.edu/~wec47/famldcaller.html.

Original languageEnglish (US)
Article number37
JournalBMC bioinformatics
Issue number1
StatePublished - Jan 16 2016

Bibliographical note

Funding Information:
This study is supported by the research grants R01HG007358 (W.C.), R01HG006857 (B.L.) and R01DA024417 (W.G.L.) from National Institute of Health. We thank Goncalo Abecasis and Mary Kate in the Department of Biostatistics at the University of Michigan for sharing the C++ libraries for processing VCF files and pedigrees. We also thank Daniel Weeks in the Department of Human Genetics at the University of Pittsburgh for useful comments on the manuscript.

Publisher Copyright:
© 2016 Chang et al.


  • Family-based sequencing
  • Genotype calling
  • Hidden Markov model


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