Evidence map›Paper›PMID 32912314›Full record

ArticleGenome biology2020

sn-spMF: matrix factorization informs tissue-specific genetic regulation of gene expression.

Yuan He, Surya B Chhetri, Marios Arvanitis, Kaushik Srinivasan, François Aguet, Kristin G Ardlie, Alvaro N Barbeira, Rodrigo Bonazzola, Hae Kyung Im, GTEx Consortium and 2 more

Open access · goldAbstract readEvaluation Study
In one paragraph

Article in Genome biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
3.2field-weighted citation impact, top 8% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed, 32 citations in OpenAlex.

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  13. EEF1A1 transcription cofactor gene polymorphism is associated with muscle gene expression and residual feed intake in Nelore cattle.Mammalian genome : official journal of the International Mammalian Genome Society · 2022
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors at 4 institutions in 1 country.

Yuan HeDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, 21218, MD, USA.
Surya B ChhetriHudsonAlpha Institute for Biotechnology, Huntsville, 35806, AL, USA.
Marios ArvanitisDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, 21218, MD, USA.
Kaushik SrinivasanDepartment of Computer Science, Johns Hopkins University, Baltimore, 21218, MD, USA.
François AguetThe Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Kristin G ArdlieThe Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Alvaro N BarbeiraSection of Genetic Medicine, Department of Medicine, The University of Chicago, Chicago, IL, USA.
Rodrigo BonazzolaSection of Genetic Medicine, Department of Medicine, The University of Chicago, Chicago, IL, USA.
Hae Kyung ImSection of Genetic Medicine, Department of Medicine, The University of Chicago, Chicago, IL, USA.
GTEx Consortium
Christopher D BrownDepartment of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, 19104, PA, USA. chrbro@pennmedicine.upenn.edu.
Alexis BattleDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, 21218, MD, USA. ajbattle@jhu.edu.ORCID 0000-0002-5287-627X
Johns Hopkins University · USUniversity of Chicago · USBroad Institute · USUniversity of Pennsylvania · US

Funding

PATHOPHYSIOLOGY OF MYOCARDIAL DISEASEST32HL007227 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI Chulan Kwon, WENDY S POST · 1985 to 2026
$21.2M
Pilot and Feasibility ProgramP30DK020595 · NIDDK · UNIVERSITY OF CHICAGO · PI Raghavendra G Mirmira · 2013 to 2026
$20.9M
A portal and integrative collaborative analysis platform for GTExU41HG009494 · NHGRI · BROAD INSTITUTE, INC. · PI ARDLIE, KRISTIN, GETZ, GAD A · 2017 to 2021
$5.2M
Epigenetic fine-mapping of cardiometabolic disease loci in the human liverR01HL133218 · NHLBI · UNIVERSITY OF PENNSYLVANIA · PI BROWN, CHRISTOPHER DAVID, ENGELHARDT, BARBARA · 2017 to 2020
$3.1M
Robust Methods for Polygenic Analysis to Inform Disease Etiology and Enhance Risk PredictionR01HG010480 · NHGRI · JOHNS HOPKINS UNIVERSITY · PI CHATTERJEE, NILANJAN · 2019 to 2023
$2.8M
Predicted Gene Expression: High Power, Mechanism, and Direction of EffectR01MH107666 · NIMH · UNIVERSITY OF CHICAGO · PI IM, HAE KYUNG · 2015 to 2017
$1.3M
3/3 Building integrative CNS networks for genomic analysis of autismR01MH109905 · NIMH · JOHNS HOPKINS UNIVERSITY · PI BATTLE, ALEXIS · 2016 to 2020
$1.2M
NCI NIH HHS HHSN261200800001ENHGRI NIH HHS R01 HG010480NHGRI NIH HHS U41 HG009494NHLBI NIH HHS HHSN268201000029CNHLBI NIH HHS R01 HL133218NHLBI NIH HHS T32 HL007227NIDDK NIH HHS P30 DK020595NIMH NIH HHS R01 MH107666NIMH NIH HHS R01 MH109905
6 · The paper itself

Abstract

Genetic regulation of gene expression, revealed by expression quantitative trait loci (eQTLs), exhibits complex patterns of tissue-specific effects. Characterization of these patterns may allow us to better understand mechanisms of gene regulation and disease etiology. We develop a constrained matrix factorization model, sn-spMF, to learn patterns of tissue-sharing and apply it to 49 human tissues from the Genotype-Tissue Expression (GTEx) project. The learned factors reflect tissues with known biological similarity and identify transcription factors that may mediate tissue-specific effects. sn-spMF, available at https://github.com/heyuan7676/ts_eQTLs , can be applied to learn biologically interpretable patterns of eQTL tissue-specificity and generate testable mechanistic hypotheses.

Indexed as

Gene Expression RegulationModels, GeneticQuantitative Trait LociHumansTranscription FactorsTranscription FactorsMatrix factorizationTissue-specific eQTLsTranscription factorsUbiquitous eQTLs

Identifiers

PMID32912314
PMCPMC7488540
OpenAlexW3083805655

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.