QCAT: testing causality of variants using only summary association statistics
By
Donghyung Lee,
T. Bernard Bigdeli,
Vladimir I Vladimirov,
Ayman H. Fanous,
Silviu-Alin Bacanu
Posted 30 Aug 2016
bioRxiv DOI: 10.1101/072355
Genome-wide and, very soon, sequencing association studies, might yield multiple regions harbouring interesting association signals. Given that each region encompasses numerous variants in high linkage disequilibrium, it is not clear which are i) truly causal or ii) just reasonably close to the causal ones. Researchers proposed many methods to predict, albeit not test, the causal SNPs in a region, a process commonly denoted as fine-mapping. Unfortunately, all existing fine-mapping methods output posterior causality probabilities assuming that causal SNPs are among those already measured in the study, or have been catalogued elsewhere. However, due to technological and computational obstacles in calling many types of genetic variants, such assumption is not realistic. We propose a novel method/software, denoted as Quasi-CAausality Test (QCAT), for testing (not just predicting) the causality of any catalogued genetic variant. QCAT i) makes no assumption that causal variants are among catalogued variants, and ii) makes use of easily available summary statistics from genetic studies, e.g. variant association Z-scores, to make statistical inferences. The proposed statistical test controls the type I error at or below the desired level. Its practical application to well-known smoking association signals provide some insightful results.
Download data
- Downloaded 790 times
- Download rankings, all-time:
- Site-wide: 27,405
- In genetics: 1,362
- Year to date:
- Site-wide: 75,867
- Since beginning of last month:
- Site-wide: 75,867
Altmetric data
Downloads over time
Distribution of downloads per paper, site-wide
PanLingua
News
- 27 Nov 2020: The website and API now include results pulled from medRxiv as well as bioRxiv.
- 18 Dec 2019: We're pleased to announce PanLingua, a new tool that enables you to search for machine-translated bioRxiv preprints using more than 100 different languages.
- 21 May 2019: PLOS Biology has published a community page about Rxivist.org and its design.
- 10 May 2019: The paper analyzing the Rxivist dataset has been published at eLife.
- 1 Mar 2019: We now have summary statistics about bioRxiv downloads and submissions.
- 8 Feb 2019: Data from Altmetric is now available on the Rxivist details page for every preprint. Look for the "donut" under the download metrics.
- 30 Jan 2019: preLights has featured the Rxivist preprint and written about our findings.
- 22 Jan 2019: Nature just published an article about Rxivist and our data.
- 13 Jan 2019: The Rxivist preprint is live!