Evidence map›Paper›PMID 32268109›Full record

ArticleCell metabolism2020

Systematically Sifting Big Data to Identify Novel Causal Genes for Human Traits.

Nicholas J Hand, Daniel J Rader

Abstract readComment
PubMed Publisher
In one paragraph

Article in Cell metabolism, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Nicholas J HandDepartment of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Daniel J RaderDepartment of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Electronic address: rader@pennmedicine.upenn.edu.

Funding

iPS-derived hepatocytes for interrogation of lipid phenotypesU01HG006398 · NHGRI · UNIVERSITY OF PENNSYLVANIA · PI RADER, DANIEL JAMES · 2011 to 2015
$8.6M
Molecular mechanisms and pathways of novel genomic loci regulating plasma lipidsRC2HL101864 · NHLBI · UNIVERSITY OF PENNSYLVANIA · PI RADER, DANIEL JAMES · 2009 to 2010
$4.7M
HDL metabolism: Influence of extracellular lipasesR37HL055323 · NHLBI · UNIVERSITY OF PENNSYLVANIA · PI RADER, DANIEL JAMES · 2009 to 2018
$4.0M
Genetics of Elevated High Density Lipoprotein CholesterolR01HL089309 · NHLBI · UNIVERSITY OF PENNSYLVANIA · PI RADER, DANIEL JAMES · 2008 to 2012
$3.9M
Molecular mechanisms underlying the genetic association between PPP1R3B and hepatic steatosisR01DK114291 · NIDDK · UNIVERSITY OF PENNSYLVANIA · PI BAUR, JOSEPH A., RADER, DANIEL JAMES · 2018 to 2021
$2.9M
NHGRI NIH HHS U01 HG006398NHLBI NIH HHS R01 HL089309NHLBI NIH HHS R37 HL055323NHLBI NIH HHS RC2 HL101864NIDDK NIH HHS R01 DK114291
6 · The paper itself

Abstract

Widespread technological advances have propelled human genetics into a "big data" era, in which genome-wide data from extremely large cohorts can be integrated with other "-omics" datasets from humans and model systems. Li et al. (2020) demonstrate the power of applying multiple computational analyses to publicly available data to prioritize the study of genes with novel trait associations.

Indexed as

Genome-Wide Association StudyHuman GeneticsAnimalsBig DataCholesterolHumansMicePhenotypeCholesterol

Identifiers

PMID32268109

What OpenQuestion holds

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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.