irGSEA: the integration of single-cell rank-based gene set enrichment analysis

IrGSEA is an R package designed to assess the outcomes of various gene set scoring methods when applied to single-cell RNA sequencing data. This package incorporates six distinct scoring methods that rely on the expression ranks of genes, emphasizing relative expression levels over absolute values. The implemented methods include AUCell, UCell, singscore, ssGSEA, JASMINE and Viper. Previous studies have demonstrated the robustness of these methods to variations in dataset size and composition, generating enrichment scores based solely on the relative gene expression of individual cells. By employing the robust rank aggregation algorithm, irGSEA amalgamates results from all six methods to ascertain the…

• NN
  National Natural Science Foundation of China

  Award: 81070478
• UD
  Universidade de Macau
• SP
  Sanming Project of Medicine in Shenzhen

  Award: SZSM 202011005
• SA
  Science and Technology Planning Project of Guangdong Province

  Award: 2020-53-112