The processed proteomics 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 8769 rows and 10 columns.
Examples
data(tissue_tvn_proteomics)
head(tissue_tvn_proteomics)
#> # 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 0.594 6.45e-19 1.77e-18 9.98 MDE
#> 2 PLXND1 23129 0.596 6.59e-38 4.17e-37 16.5 MDE
#> 3 MPO 4353 0.504 1.22e- 9 2.23e- 9 6.42 MDE
#> 4 IL32 9235 0.878 1.25e-12 2.63e-12 7.64 MDE
#> 5 TRAF3IP3 80342 0.518 3.30e-15 7.78e-15 8.63 MDE
#> 6 STAB1 23166 0.547 5.59e-16 1.36e-15 8.92 MDE
#> # ℹ 3 more variables: `SiRCleThreshold_DNA-Methylation` <chr>,
#> # SiRCleThreshold_RNA <chr>, SiRCleThreshold_Protein <chr>