PuSH - Publikationsserver des Helmholtz Zentrums München: Large eQTL meta-analysis reveals differing patterns between cerebral cortical and cerebellar brain regions.

Informationen

Hinweise zu Qualitätskriterien von Zeitschriften

Open-Access-Richtlinie der Helmholtz-Gemeinschaft 2016

CC Licencences

Metriken für Publikationen

Navigation

Startseite

English

Recherche

Erweiterte Suche

Durchblättern nach ...

... HMGU-Autoren/Konsortien

... Organisationsstruktur

... Zeitschriften

... Publikationstypen

... Forschungsdaten

... Arbeitsgruppen

... Erscheinungsjahr

Publikationen im Überblick

Statistik

HGF Fortschrittsbericht

OA Publikationen

Eintragen

Neue Publikation eintragen

Neue Publikation holen aus...

...EVA

Fehlende Publikation melden

Highlights

Suche

Hilfe & Kontakt

Ansprechpartner

Hilfe

Datenschutz

Helmholtz Open Science

Bibliometrische Indikatoren

SHERPA/RoMEO

DOAJ

Export:

Text

Endnote (RIS) BIB

BibTeX

Sieberts, S.K.* ; Perumal, T.M.* ; Carrasquillo, M.M.* ; Allen, M.* ; Reddy, J.S.* ; Hoffman, G.E.* ; Dang, K.K.* ; Calley, J.* ; Ebert, P.J.* ; Eddy, J.* ; Wang, X.* ; Greenwood, A.K.* ; Mostafavi, S.* ; Omberg, L.* ; Peters, M.A.* ; Logsdon, B.A.* ; de Jager, P.L.* ; Ertekin-Taner, N.* ; Mangravite, L.M.* ; The AMP-AD Consortium (Arnold, M.)

Large eQTL meta-analysis reveals differing patterns between cerebral cortical and cerebellar brain regions.

Sci. Data 7:340 (2020)

Verlagsversion

DOI

PMC

	Open Access Gold

Abstract
Metriken
Zusatzinfos

The availability of high-quality RNA-sequencing and genotyping data of post-mortem brain collections from consortia such as CommonMind Consortium (CMC) and the Accelerating Medicines Partnership for Alzheimer’s Disease (AMP-AD) Consortium enable the generation of a large-scale brain cis-eQTL meta-analysis. Here we generate cerebral cortical eQTL from 1433 samples available from four cohorts (identifying >4.1 million significant eQTL for >18,000 genes), as well as cerebellar eQTL from 261 samples (identifying 874,836 significant eQTL for >10,000 genes). We find substantially improved power in the meta-analysis over individual cohort analyses, particularly in comparison to the Genotype-Tissue Expression (GTEx) Project eQTL. Additionally, we observed differences in eQTL patterns between cerebral and cerebellar brain regions. We provide these brain eQTL as a resource for use by the research community. As a proof of principle for their utility, we apply a colocalization analysis to identify genes underlying the GWAS association peaks for schizophrenia and identify a potentially novel gene colocalization with lncRNA RP11-677M14.2 (posterior probability of colocalization 0.975).

Impact Factor

Scopus SNIP

Scopus
Cited By

Altmetric

5.541

2.887