The quality of the sequenced reads was assessed with FastQC and QoRTs. Unless stated otherwise, plots involving high-throughput sequencing data were created using R and ggplot2.
Reads were aligned to the mouse reference genome (GRCm38.p6) using STAR v2.7.9a with default parameters. Gene abundances were calculated with featureCounts v2.0.1 using composite gene models from Gencode release vM25. Differentially expressed genes were identified using DESeq2 v1.42.0 with a two-factor model incorporating sex as a covariate, with significance determined by Wald tests (q < 0.01). Gene set enrichment analysis was performed using fgsea v1.28.0 with M8 cell type signature gene sets from the Broad Institute’s MSigDB collections; genes were ranked by the DESeq2 Wald statistic. Only pathways with an adjusted P value < 0.05 were considered enriched. Over-representation testing of gene ontology terms (GO) was performed using clusterProfiler v4.10.1 (q < 0.05) Expression heatmaps were generated using variance-stabilized data, with the values centered and scaled by row.
| Software | Version | Authors | URL |
|---|---|---|---|
| STAR | v2.7.9a | Dobin et al. | GitHub |
| featureCounts | v2.0.1 | Liao et al. | Subread |
| R | v4.3.2 | R Core Team | CRAN |
| DESeq2 | v1.42.0 | Love et al. | Bioconductor |
| ggplot2 | v3.4.4 | Wickham | CRAN |
| pheatmap | v1.0.12 | Kolde | CRAN |
| fgsea | v1.28.0 | Korotkevich et al. | Bioconductor |
| clusterProfiler | v4.10.1 | Guangchuang et al. | Bioconductor |