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Genet Epidemiol. 2018 Feb;42(1):123-126. doi: 10.1002/gepi.22094. Epub 2017 Nov 21.

Family-based tests for associating haplotypes with general phenotype data: Improving the FBAT-haplotype algorithm.

Author information

1
Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America.
2
Department of Genomic Mathematics, University of Bonn, Bonn, Germany.
3
Nanfang Hospital, Southern Medical University, Guangzhou, China.
4
Department of Mathematics and Statistics, Utah State University, Logan, UT, USA.
5
Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA.

Abstract

For family-based association studies, Horvath et al. proposed an algorithm for the association analysis between haplotypes and arbitrary phenotypes when the phase of the haplotypes is unknown, that is, genotype data is given. Their approach to haplotype analysis maintains the original features of the TDT/FBAT-approach, that is, complete robustness against genetic confounding and misspecification of the phenotype. The algorithm has been implemented in the FBAT and PBAT software package and has been used in numerous substantive manuscripts. Here, we propose a simplification of the original algorithm that maintains the original approach but reduces the computational burden of the approach substantially and gives valuable insights regarding the conditional distribution. With the modified algorithm, the application to whole-genome sequencing (WGS) studies becomes feasible; for example, in sliding window approaches or spatial-clustering approaches. The reduction of the computational burden that our modification provides is especially dramatic when both parental genotypes are missing. For example, for eight variants and 441 nuclear families with mostly offspring-only families, in a WGS study at the APOE locus, the running time decreased from approximately 21 hr for the original algorithm to 0.11 sec after our modification.

KEYWORDS:

FBAT; admixture; candidate region; whole-genome sequencing

PMID:
29159827
PMCID:
PMC5774664
[Available on 2019-02-01]
DOI:
10.1002/gepi.22094
[Indexed for MEDLINE]

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