scholarly journals Challenging False Discovery Rate: A Partition Test Based on p Values in Human Case-Control Association Studies

2012 ◽  
Vol 74 (1) ◽  
pp. 45-50 ◽  
Author(s):  
Jurg Ott ◽  
Zhe Liu ◽  
Yuanyuan Shen
Keyword(s):  
False Discovery Rate ◽  
Association Studies ◽  
Human Case ◽  
Case Control ◽  
P Values ◽  
False Discovery ◽  
Partition Test ◽  
Control Association

scholarly journals A Pleiotropy-Informed Bayesian False Discovery Rate adapted to a Shared Control Design Finds New Disease Associations From GWAS Summary Statistics

2015 ◽  
Author(s):  
James Liley ◽  
Chris Wallace
Keyword(s):  
False Discovery Rate ◽  
Upper Bound ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Summary Statistics ◽  
Nucleotide Polymorphisms ◽  
P Values ◽  
Replication Studies ◽  
False Discovery ◽  
Disease Associations

Genome-wide association studies (GWAS) have been successful in identifying single nucleotide polymorphisms (SNPs) associated with many traits and diseases. However, at existing sample sizes, these variants explain only part of the estimated heritability. Leverage of GWAS results from related phenotypes may improve detection without the need for larger datasets. The Bayesian conditional false discovery rate (cFDR) constitutes an upper bound on the expected false discovery rate (FDR) across a set of SNPs whose p values for two diseases are both less than two disease-specific thresholds. Calculation of the cFDR requires only summary statistics and has several advantages over traditional GWAS analysis. However, existing methods require distinct control samples between studies. Here, we extend the technique to allow for some or all controls to be shared, increasing applicability. Several different SNP sets can be defined with the same cFDR value, and we show that the expected FDR across the union of these sets may exceed expected FDR in any single set. We describe a procedure to establish an upper bound for the expected FDR among the union of such sets of SNPs. We apply our technique to pairwise analysis of p values from ten autoimmune diseases with variable sharing of controls, enabling discovery of 59 SNP-disease associations which do not reach GWAS significance after genomic control in individual datasets. Most of the SNPs we highlight have previously been confirmed using replication studies or larger GWAS, a useful validation of our technique; we report eight SNP-disease associations across five diseases not previously declared. Our technique extends and strengthens the previous algorithm, and establishes robust limits on the expected FDR. This approach can improve SNP detection in GWAS, and give insight into shared aetiology between phenotypically related conditions.

scholarly journals Leveraging Family History in Population-Based Case-Control Association Studies

2014 ◽  
Vol 38 (2) ◽  
pp. 114-122 ◽  
Author(s):  
Arpita Ghosh ◽  
Patricia Hartge ◽  
Peter Kraft ◽  
Amit D. Joshi ◽  
Regina G. Ziegler ◽  
...  
Keyword(s):  
Family History ◽  
Association Studies ◽  
Population Based ◽  
Case Control ◽  
Control Association

A Retrospective Likelihood Approach for Efficient Integration of Multiple Omics Factors in Case-Control Association Studies

2015 ◽  
Vol 39 (3) ◽  
pp. 156-165 ◽  
Author(s):  
Brunilda Balliu ◽  
Roula Tsonaka ◽  
Stefan Boehringer ◽  
Jeanine Houwing-Duistermaat
Keyword(s):  
Association Studies ◽  
Case Control ◽  
Efficient Integration ◽  
Retrospective Likelihood ◽  
Likelihood Approach ◽  
Control Association
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