Abstract

Sequencing cases without matched healthy controls hinders prioritization of germline disease-predisposition genes. To circumvent this problem, genotype summary counts from public data sets can serve as controls. However, systematic inflation and false positives can arise if confounding factors are not controlled. We propose a framework, consistent summary counts based rare variant burden test (CoCoRV), to address these challenges. CoCoRV implements consistent variant quality control and filtering, ethnicity-stratified rare variant association test, accurate estimation of inflation factors, powerful FDR control, and detection of rare variant pairs in high linkage disequilibrium. When we applied CoCoRV to pediatric cancer cohorts, the top genes identified were cancer-predisposition genes. We also applied CoCoRV to identify disease-predisposition genes in adult brain tumors and amyotrophic lateral sclerosis. Given that potential confounding factors were well controlled after applying the framework, CoCoRV provides a cost-effective solution to prioritizing disease-risk genes enriched with rare pathogenic variants.

Sequencing studies in clinical and cancer genomics often utilize public data sets to identify genes enriched with pathogenic variants. Here, the authors propose a framework which controls for confounding factors that can bias the results in these studies.

Details

Title
A rare variant analysis framework using public genotype summary counts to prioritize disease-predisposition genes
Author
Chen, Wenan 1   VIAFID ORCID Logo  ; Wang Shuoguo 2 ; Tithi Saima Sultana 3 ; Ellison, David W 4 ; Schaid, Daniel J 5 ; Wu, Gang 6   VIAFID ORCID Logo 

 St. Jude Children’s Research Hospital, Center for Applied Bioinformatics, Memphis, USA (GRID:grid.240871.8) (ISNI:0000 0001 0224 711X) 
 St. Jude Children’s Research Hospital, Department of Computational Biology, Memphis, USA (GRID:grid.240871.8) (ISNI:0000 0001 0224 711X); 150 Second Street, Cambridge, USA (GRID:grid.240871.8) 
 St. Jude Children’s Research Hospital, Department of Cell & Molecular Biology, Memphis, USA (GRID:grid.240871.8) (ISNI:0000 0001 0224 711X) 
 St. Jude Children’s Research Hospital, Department of Pathology, Memphis, USA (GRID:grid.240871.8) (ISNI:0000 0001 0224 711X) 
 Mayo Clinic, Department of Quantitative Health Sciences, Rochester, USA (GRID:grid.66875.3a) (ISNI:0000 0004 0459 167X) 
 St. Jude Children’s Research Hospital, Center for Applied Bioinformatics, Memphis, USA (GRID:grid.240871.8) (ISNI:0000 0001 0224 711X); St. Jude Children’s Research Hospital, Department of Pathology, Memphis, USA (GRID:grid.240871.8) (ISNI:0000 0001 0224 711X) 
Publication year
2022
Publication date
2022
Publisher
Nature Publishing Group
e-ISSN
20411723
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2662181096
Copyright
© The Author(s) 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.