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

We 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.

The 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.

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.