| Title: |
A correction for sample overlap in genome-wide association studies in a polygenic pleiotropy-informed framework |
| Authors: |
LeBlanc, M; Zuber, V; Thompson, WK; Andreassen, OA; Frigessi, A; Andreassen, BK; Ripke, S; Neale, BM; Corvin, A; Walters, JTR; Farh, KH; Lee, P; Bulik-Sullivan, B; Collier, DA; Huang, H; Pers, TH; Agartz, I; Agerbo, E; Albus, M; Alexander, M; Amin, F; Bacanu, SA; Begemann, M; Belliveau, RA; Bene, J; Bevilacqua, E; Bigdeli, TB; Black, DW; Bruggeman, R; Buccola, NG; Buckner, RL; Cahn, W; Cai, G; Cairns, MJ; Campion, D; Cantor, RM; Carr, VJ; Carrera, N; Catts, SV; Chambert, KD; Chan, RCK; Chen, RYL; Chen, EYH; Cheng, W; Cheung, EFC; Chong, SA; Cloninger, CR; Cohen, D; Cohen, N; Cormican, P; Craddock, N; Crespo-Facorro, B; Crowley, JJ; Curtis, D; Davidson, M; Davis, KL; Degenhardt, F; Favero, JD; DeLisi, LE; Demontis, D; Dikeos, D; Dinan, T; Donohoe, G; Drapeau, E; Duan, J; Dudbridge, F; Durmishi, N; Eichhammer, P; Eriksson, J; Escott-Price, V; Essioux, L; Fanous, AH; Farrell, MS; Frank, J; Franke, L; Freedman, R; Freimer, NB; Friedl, M; Friedman, JI; Fromer, M; Genovese, G; Georgieva, L; Gershon, ES; Giegling, I; Giusti-Rodriguez, P; Godard, S; Goldstein, JI; Golimbet, V; Gopal, S; Gratten, J; de Haan, L; Hammer, C; Hamshere, ML; Hansen, M; Hansen, T; Haroutunian, V; Hartmann, AM; Henskens, FA; Herms, S; Hirschhorn, JN; Mitchell, Philip; Schofield, Peter |
| Source: |
urn:ISSN:1471-2164 ; BMC Genomics, 19, 1, 494 |
| Publisher Information: |
Springer Nature |
| Publication Year: |
2018 |
| Collection: |
UNSW Sydney (The University of New South Wales): UNSWorks |
| Subject Terms: |
31 Biological Sciences; 3105 Genetics; Genetics; Human Genome; 1.4 Methodologies and measurements; Case-Control Studies; Computer Simulation; Genome-Wide Association Study; Genotype; Humans; Phenotype; Polymorphism; Single Nucleotide; Covariate-modulated false discovery rate; Cross-phenotype association; Data integration; Meta-analysis with shared subjects; Schizophrenia and Bipolar Disorder Working Groups of the Psychiatric Genomics Consortium; anzsrc-for: 31 Biological Sciences; anzsrc-for: 3105 Genetics; anzsrc-for: 06 Biological Sciences; anzsrc-for: 08 Information and Computing Sciences; anzsrc-for: 11 Medical and Health Sciences; anzsrc-for: 32 Biomedical and clinical sciences |
| Description: |
Background: There is considerable evidence that many complex traits have a partially shared genetic basis, termed pleiotropy. It is therefore useful to consider integrating genome-wide association study (GWAS) data across several traits, usually at the summary statistic level. A major practical challenge arises when these GWAS have overlapping subjects. This is particularly an issue when estimating pleiotropy using methods that condition the significance of one trait on the signficance of a second, such as the covariate-modulated false discovery rate (cmfdr). Results: We propose a method for correcting for sample overlap at the summary statistic level. We quantify the expected amount of spurious correlation between the summary statistics from two GWAS due to sample overlap, and use this estimated correlation in a simple linear correction that adjusts the joint distribution of test statistics from the two GWAS. The correction is appropriate for GWAS with case-control or quantitative outcomes. Our simulations and data example show that without correcting for sample overlap, the cmfdr is not properly controlled, leading to an excessive number of false discoveries and an excessive false discovery proportion. Our correction for sample overlap is effective in that it restores proper control of the false discovery rate, at very little loss in power. Conclusions: With our proposed correction, it is possible to integrate GWAS summary statistics with overlapping samples in a statistical framework that is dependent on the joint distribution of the two GWAS. |
| Document Type: |
article in journal/newspaper |
| File Description: |
application/pdf |
| Language: |
unknown |
| Relation: |
https://hdl.handle.net/1959.4/unsworks_56625 |
| DOI: |
10.1186/s12864-018-4859-7 |
| Availability: |
https://hdl.handle.net/1959.4/unsworks_56625; https://unsworks.unsw.edu.au/bitstreams/c984840d-1807-4aad-9afe-54d19c1d9264/download; https://doi.org/10.1186/s12864-018-4859-7 |
| Rights: |
open access ; https://purl.org/coar/access_right/c_abf2 ; CC BY ; https://creativecommons.org/licenses/by/4.0/ ; free_to_read |
| Accession Number: |
edsbas.6DD2550F |
| Database: |
BASE |