The processed transcriptomics data was downloaded from the supplementary table 3 of Mora & Schmidt et. al., which used the study from Clark et. al. under Proteomics data Commons PDC000127. on their regulation regulation in renal cancer, Genome Medicine 2024, doi:10.1186/s13073-024-01415-3 Clark et. al, Integrated proteogenomic characterization of clear cell renal cell carcinoma, Cell 2019, doi:10.1016/j.cell.2019.10.007
Format
An object of class spec_tbl_df (inherits from tbl_df, tbl, data.frame) with 29283 rows and 10 columns.
Examples
data(tissue_tvn_rnaseq)
head(tissue_tvn_rnaseq)
#> # A tibble: 6 × 10
#> gene_name entrezgene_id Log2FC p.val p.adj t.val SiRCleCluster_RG2
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <chr>
#> 1 FGR 2268 2.02 4.23e-90 8.96e-89 20.1 MDE
#> 2 PLXND1 23129 1.54 1.27e-99 3.39e-98 21.2 MDE
#> 3 MPO 4353 1.26 1.55e- 8 2.93e- 8 5.66 MDE
#> 4 IL32 9235 1.13 1.77e-23 6.10e-23 9.99 MDE
#> 5 TRAF3IP3 80342 1.46 1.02e-49 7.58e-49 14.8 MDE
#> 6 STAB1 23166 1.61 2.68e-54 2.26e-53 15.5 MDE
#> # ℹ 3 more variables: `SiRCleThreshold_DNA-Methylation` <chr>,
#> # SiRCleThreshold_RNA <chr>, SiRCleThreshold_Protein <chr>