Evidence map›Paper›PMID 40253343›Full record

ArticleBMC bioinformatics2025

metacp: a versatile software package for combining dependent or independent p-values.

Evgenia K Nikolitsa, Panagiota I Kontou, Pantelis G Bagos

Abstract read
In one paragraph

Article in BMC bioinformatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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4 · The record

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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

3 authors.

Evgenia K NikolitsaDepartment of Computer Science and Biomedical Informatics, University of Thessaly, 35100, Lamia, Greece.
Panagiota I KontouDepartment of Mathematics, University of Thessaly, 35100, Lamia, Greece.
Pantelis G BagosDepartment of Computer Science and Biomedical Informatics, University of Thessaly, 35100, Lamia, Greece. pbagos@compgen.org.

Funding

NextGenerationEU TAEDR-0539180
6 · The paper itself

Abstract

backgroundWe present metacp an open-source software package which implements an abundance of statistical methods for the combination of both independent p-values, with methods such as Fisher's, Stouffer's and Edgington's, and dependent p-values, with methods such as Brown's method and the Cauchy Combination Test.

resultsThe tool is available in Python and STATA, it is very fast, and it is easy to use, requiring only minimal input. It offers a useful resource for combining both independent and dependent p-values, responding to diverse analytical needs for practitioners performing meta-analyses and bioinformaticians developing tools for a variety of applications. Depending on the input data it can be used for gene-based testing, for analysis of multiple traits in GWAS, or for combining diverse multi-omics data such as those of a TWAS, a colocalization or an RNA-seq study.

conclusionsCompared to other similar packages (like poolr or metap), metacp implements the largest collection of statistical methods for this problem, offering users the flexibility to choose from a wide variety of approaches. Being available both as a standalone Python tool and as a STATA command, metacp is accessible to a broad and diverse audience, including practitioners conducting meta-analyses across various fields and bioinformaticians developing new tools where p-value combination is a crucial component.

Indexed as

Computational BiologySoftwareGenome-Wide Association StudyHumansGWAS meta-analysisMetacpMulti-omics analysisp-values combination

Identifiers

PMID40253343
PMCPMC12008841

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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.