2.4. Signature Analysis

To assess the similarities between gene expression signatures, we employed Pearson correlation, provided by the R basic function cor().

For the pathway enrichment analysis, we retrieved gene sets from KEGG, WikiPathways and Gene Ontology using the Molecular Signatures Database (MSigDB) [65]. We accessed the database via the R package msigdbr version 7.5.1 and implemented the enrichment analysis on the signatures using the R package fgsea version 1.24.0. This package uses an algorithm for expedited and parallel gene set enrichment analysis [66].

To integrate the normalized enrichment scores (NES) derived from the pathway enrichment analysis, we employed Stouffer integration as implemented by the corto R package version 1.2.0 [55] and as performed before [61]. Z-scores were converted to p-values, where needed, using the z2p() function from the aforementioned corto package [55]. All p-values were corrected using the Benjamini–Hochberg method. All the R code used to integrate data and generate the figures in this paper is available on Github at the following address: https://github.com/federicogiorgi/pfas (accessed on 14 June 2023).