PTWAS: investigating tissue-relevant causal molecular mechanisms of complex traits using probabilistic TWAS analysis.
Causal inference
GWAS
Genetic association
Instrumental variable
TWAS
eQTLs
Journal
Genome biology
ISSN: 1474-760X
Titre abrégé: Genome Biol
Pays: England
ID NLM: 100960660
Informations de publication
Date de publication:
11 09 2020
11 09 2020
Historique:
received:
29
10
2019
accepted:
20
04
2020
entrez:
11
9
2020
pubmed:
12
9
2020
medline:
16
6
2021
Statut:
epublish
Résumé
We propose a new computational framework, probabilistic transcriptome-wide association study (PTWAS), to investigate causal relationships between gene expressions and complex traits. PTWAS applies the established principles from instrumental variables analysis and takes advantage of probabilistic eQTL annotations to delineate and tackle the unique challenges arising in TWAS. PTWAS not only confers higher power than the existing methods but also provides novel functionalities to evaluate the causal assumptions and estimate tissue- or cell-type-specific gene-to-trait effects. We illustrate the power of PTWAS by analyzing the eQTL data across 49 tissues from GTEx (v8) and GWAS summary statistics from 114 complex traits.
Identifiants
pubmed: 32912253
doi: 10.1186/s13059-020-02026-y
pii: 10.1186/s13059-020-02026-y
pmc: PMC7488550
doi:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Validation Study
Langues
eng
Sous-ensembles de citation
IM
Pagination
232Subventions
Organisme : NIGMS NIH HHS
ID : R01 GM109215
Pays : United States
Organisme : NIGMS NIH HHS
ID : R35 GM138121
Pays : United States
Organisme : NIEHS NIH HHS
ID : T32 ES007142
Pays : United States
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