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Estimation of non-n...
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Ramachandran, SohiniUppsala universitet,Kollegiet för avancerade studier (SCAS)
(author)
Estimation of non-null SNP effect size distributions enables the detection of enriched genes underlying complex traits
- Article/chapterEnglish2020
Publisher, publication year, extent ...
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2020-06-15
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Public Library of Science (PLoS),2020
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printrdacarrier
Numbers
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LIBRIS-ID:oai:DiVA.org:uu-433059
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https://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-433059URI
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https://doi.org/10.1371/journal.pgen.1008855DOI
Supplementary language notes
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Language:English
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Summary in:English
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Subject category:ref swepub-contenttype
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Subject category:art swepub-publicationtype
Notes
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Traditional univariate genome-wide association studies generate false positives and nega-tives due to difficulties distinguishing associated variants from variants with spurious non-zero effects that do not directly influence the trait. Recent efforts have been directed atidentifying genes or signaling pathways enriched for mutations in quantitative traits or case-control studies, but these can be computationally costly and hampered by strict modelassumptions. Here, we present gene-ε, a new approach for identifying statistical associa-tions between sets of variants and quantitative traits. Our key insight is that enrichment stud-ies on the gene-level are improved when we reformulate the genome-wide SNP-level nullhypothesis to identify spurious small-to-intermediate SNP effects and classify them as non-causal. gene-ε efficiently identifies enriched genes under a variety of simulated geneticarchitectures, achieving greater than a 90% true positive rate at 1% false positive rate forpolygenic traits. Lastly, we apply gene-ε to summary statistics derived from six quantitativetraits using European-ancestry individuals in the UK Biobank, and identify enriched genesthat are in biologically relevant pathways.
Added entries (persons, corporate bodies, meetings, titles ...)
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Cheng, Wei
(author)
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Crawford, Lorin
(author)
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Uppsala universitetKollegiet för avancerade studier (SCAS)
(creator_code:org_t)
Related titles
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In:PLOS Genetics: Public Library of Science (PLoS)16:61553-73901553-7404
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