PT - JOURNAL ARTICLE AU - Alexandre Bureau AU - Ferdouse Begum AU - Margaret A. Taub AU - Jacqueline Hetmanski AU - Margaret M. Parker AU - Hasan Albacha-Hejazi AU - Alan F. Scott AU - Jeffrey C. Murray AU - Mary L. Marazita AU - Joan E. Bailey-Wilson AU - Terri H. Beaty AU - Ingo Ruczinski TI - Inferring Disease Risk Genes from Sequencing Data in Multiplex Pedigrees Through Sharing of Rare Variants AID - 10.1101/285874 DP - 2018 Jan 01 TA - bioRxiv PG - 285874 4099 - http://biorxiv.org/content/early/2018/07/11/285874.short 4100 - http://biorxiv.org/content/early/2018/07/11/285874.full AB - We previously demonstrated how sharing of rare variants (RVs) in distant affected relatives can be used to identify variants causing a complex and heterogeneous disease. This approach tested whether single RVs were shared by all sequenced affected family members. However, as with other study designs, joint analysis of several RVs (e.g. within genes) is sometimes required to obtain sufficient statistical power. Further, phenocopies can lead to false negatives for some causal RVs if complete sharing among affecteds is required. Here we extend our methodology (Rare Variant Sharing, RVS) to address these issues. Specifically, we introduce gene-based analyses, a partial sharing test based on RV sharing probabilities for subsets of affected relatives and an haplotype-based RV definition. RVS also has the desirable features of not requiring external estimates of variant frequency or control samples, provides functionality to assess and address violations of key assumptions, and is available as open source software for genome-wide analysis. Simulations including phenocopies, based on the families of an oral cleft study, revealed the partial and complete sharing versions of RVS achieved similar statistical power compared to alternative methods (RareIBD and the Gene-Based Segregation Test), and had superior power compared to the pedigree Variant Annotation, Analysis and Search Tool (pVAAST) linkage statistic. In studies of multiplex cleft families, analysis of rare single nucleotide variants in the exome of 151 affected relatives from 54 families revealed no significant excess sharing in any one gene, but highlighted different patterns of sharing revealed by the complete and partial sharing tests.