Evidence map›Paper›PMID 27587659›Full record

ArticleBioinformatics (Oxford, England)2016

Combining dependent P-values with an empirical adaptation of Brown's method.

William Poole, David L Gibbs, Ilya Shmulevich, Brady Bernard, Theo A Knijnenburg

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 78 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
78citing papers in PubMed, 3 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

78 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
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18 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

5 authors.

William PooleInstitute for Systems Biology, Seattle, WA 98109-5263, USA.
David L GibbsInstitute for Systems Biology, Seattle, WA 98109-5263, USA.
Ilya ShmulevichInstitute for Systems Biology, Seattle, WA 98109-5263, USA.
Brady BernardInstitute for Systems Biology, Seattle, WA 98109-5263, USA.
Theo A KnijnenburgInstitute for Systems Biology, Seattle, WA 98109-5263, USA.

Funding

Center for Systems Analysis of the Cancer RegulomeU24CA143835 · NCI · INSTITUTE FOR SYSTEMS BIOLOGY · PI SHMULEVICH, ILYA · 2009 to 2016
$10.6M
NCI NIH HHS U24 CA143835
6 · The paper itself

Abstract

motivationCombining P-values from multiple statistical tests is a common exercise in bioinformatics. However, this procedure is non-trivial for dependent P-values. Here, we discuss an empirical adaptation of Brown's method (an extension of Fisher's method) for combining dependent P-values which is appropriate for the large and correlated datasets found in high-throughput biology.

resultsWe show that the Empirical Brown's method (EBM) outperforms Fisher's method as well as alternative approaches for combining dependent P-values using both noisy simulated data and gene expression data from The Cancer Genome Atlas. AVAILABILITY AND IMPLEMENTATION: The Empirical Brown's method is available in Python, R, and MATLAB and can be obtained from https://github.com/IlyaLab/CombiningDependentPvalues UsingEBM The R code is also available as a Bioconductor package from https://www.bioconductor.org/packages/devel/bioc/html/EmpiricalBrownsMethod.html CONTACT: Theo.Knijnenburg@systemsbiology.org SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Indexed as

High-Throughput Screening AssaysSoftwareAlgorithmsData Interpretation, StatisticalHumansNeoplasms

Identifiers

PMID27587659
PMCPMC5013915

What OpenQuestion holds

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Registered trials

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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.