We performed differential metabolite analysis comparing ccRCC tissue versus adjacent normal tissue using median normalised data from the supplementary table 2 of Hakimi et. al.(="Tissue_Norm"). metabolite values used as input with row names being metabolite trivial names. doi:10.1016/j.ccell.2015.12.004
Format
An object of class spec_tbl_df (inherits from tbl_df, tbl, data.frame) with 570 rows and 17 columns.
Examples
data(tissue_dma)
head(tissue_dma)
#> # A tibble: 6 × 17
#> Metabolite Log2FC AveExpr t.val p.val p.adj B SUPER_PATHWAY
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <chr>
#> 1 1-arachidonoylgly… -0.433 0.0516 -2.64 8.70e- 3 1.22e- 2 -4.44 Lipid
#> 2 1-arachidonoylgly… -1.26 -0.0204 -15.4 4.88e-39 6.04e-38 77.8 Lipid
#> 3 1-arachidonoylgly… -0.968 -0.127 -11.5 2.95e-25 1.70e-24 46.2 Lipid
#> 4 1-arachidonylglyc… -0.247 -1.24 -2.46 1.43e- 2 1.94e- 2 -4.89 Lipid
#> 5 1-docosahexaenoyl… -0.915 -0.558 -6.52 3.27e-10 8.44e-10 11.9 Lipid
#> 6 1-heptadecanoylgl… -1.62 -0.353 -9.86 7.51e-20 3.48e-19 33.8 Lipid
#> # ℹ 9 more variables: SUB_PATHWAY <chr>, COMP_ID <dbl>, PLATFORM <chr>,
#> # RI <dbl>, MASS <dbl>, CAS <chr>, PUBCHEM <dbl>, KEGG <chr>,
#> # Group_HMDB <chr>