Presented at ICG12

Altmetric score 30.88 (top 3.5%)

Author: JIE ZHENG
Editor: Scott Edmunds
Type:

Open peer-review

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PhenoSpD: an atlas of phenotypic correlations and a multiple testing correction for the human phenome


Created on 10th June 2017

Jie Zheng; Tom Richardson; Louise Millard; Gibran Hemani; Chris Raistrick; Bjarni Vilhjalmsson; Philip Haycock; Tom Gaunt;


Summary: Identifying phenotypic correlations between complex traits and diseases can provide useful etiological insights. Restricted access to individual-level phenotype data makes it difficult to estimate large-scale phenotypic correlation across the human phenome. Here, we present a novel method, PhenoSpD, to estimate phenotypic correlations using genome-wide association study (GWAS) summary statistics from the same sample and utilizes the correlations to inform correction of multiple testing for human GWAS studies. In a case study using GWAS summary results, PhenoSpD suggested 324.4 independent tests among 452 metabolites, which is close to the 296 independent tests estimated using true phenotypic correlation. We then estimated 120,713 pair-wise phenotypic correlations among 24 categories of human traits and diseases (total 862 traits) and further corrected multiple testing for these traits using PhenoSpD. The atlas of phenotypic correlations provides novel insights into the relationships between traits, while the PhenoSpD multiple testing correction function provides a simple and conservative way to reduce dimensionality for GWAS of complex molecular traits. Availability: R codes and Documentation for PhenoSpD V1.0.0 is available online (https://github.com/MRCIEU/PhenoSpD).

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This paper has 0 completed reviews and 1 reviews in progress.

# Status Date
Donghyung Lee Completed 29 Aug 2017 View review
Aaron Day-Williams Completed 8 Sep 2017 View review



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