Evidence map›Paper›PMID 27070863›Full record

ReviewNature reviews. Genetics2016

The statistical properties of gene-set analysis.

Christiaan A de Leeuw, Benjamin M Neale, Tom Heskes, Danielle Posthuma

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature reviews. Genetics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 188 papers, 16 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
188citing papers in PubMed, 16 pooled it
–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

188 citing papers in PubMed, 16 syntheses or guidelines pooled it.

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  20. Integrative Multi-omics Analysis for Prioritization of Candidate Genes in Polycystic Ovary Syndrome.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2026
    Article

128 more citing papers are in PubMed but not listed here.

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

4 authors.

Christiaan A de LeeuwDepartment of Complex Trait Genetics, Centre for Neurogenomics and Cognitive Research/VU University Amsterdam, Amsterdam 1081 HV, Netherlands.
Benjamin M NealeProgram in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts 02142, USA.
Tom HeskesInstitute for Computing and Information Sciences, Radboud University Nijmegen, Nijmegen 6525 EC, Netherlands.
Danielle PosthumaDepartment of Complex Trait Genetics, Centre for Neurogenomics and Cognitive Research/VU University Amsterdam, Amsterdam 1081 HV, Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The rapid increase in loci discovered in genome-wide association studies has created a need to understand the biological implications of these results. Gene-set analysis provides a means of gaining such understanding, but the statistical properties of gene-set analysis are not well understood, which compromises our ability to interpret its results. In this Analysis article, we provide an extensive statistical evaluation of the core structure that is inherent to all gene- set analyses and we examine current implementations in available tools. We show which factors affect valid and successful detection of gene sets and which provide a solid foundation for performing and interpreting gene-set analysis.

Indexed as

Gene Expression ProfilingModels, StatisticalSoftwareAlgorithmsComputational BiologyGenome-Wide Association StudyGenomicsHumansPolymorphism, Single Nucleotide

Identifiers

PMID27070863

What OpenQuestion holds

Textmetadata
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.