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

Compared 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.

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Publication Details

Journal
BMC Bioinformatics
Published
2025-04-19
DOI
https://doi.org/10.1186/s12859-025-06126-z
Citations
1
Primary Topic
Bayesian Modeling and Causal Inference
Type
article
Field-Weighted Citation Impact
2.48

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article

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

Pantelis G. Bagos, Panagiota I. Kontou, Evgenia K Nikolitsa
1 citations
BMC Bioinformatics
Bayesian Modeling and Causal Inference
2.48
article

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

Pantelis G. Bagos, Panagiota I. Kontou, Evgenia K Nikolitsa
article en
1 citations

Abstract

Compared 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.

BMC BioinformaticsVol. 26(1)
University of Thessaly (GR)
European Commission
Openalex Percentile: Top 11%
Bayesian Modeling and Causal Inference
2.48
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