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ZENODO
Software . 2015
License: CC 0
Data sources: Datacite
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ZENODO
Software . 2015
License: CC 0
Data sources: ZENODO
Claim

A human disease network from GWAS loci

integration_instructionsResearch softwarekeyboard_double_arrow_right Software 05 Aug 2015Publisher:Zenodo
Authors: Daniel Himmelstein; Pouya Khankhanian; Sergio Baranzini;
Code repository: https://github.com/dhimmel/hodgkins/tree/v1.0

doi: 10.5281/zenodo.23025

A human disease network from GWAS loci

Abstract

We constructed a network of 82 complex human diseases. Disease similarity was calculated from overlapping GWAS loci. A random walk with restart was used to compute network proximity for all disease pairs. Autoimmune diseases and solid cancers formed distinct clusters. We contextualized three hematologic cancers against this background and found that Hodgkin's lymphoma exhibited an autoimmune genetic etiology.

Keywords

GWAS, networks, Hodgkin's lymphoma, complex disease

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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