We performed differential metabolite analysis comparing ccRCC tissue versus adjacent normal tissue of the patient's subset of old patient's (age > 58 years) 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_old)
head(tissue_dma_old)
#> # 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… -0.663 -0.0529 -3.34 1.01e- 3 1.72e- 3 -2.23 Lipid
#> 2 1-arachidonoylgly… -1.26 -0.0300 -12.4 7.73e-26 9.26e-25 47.9 Lipid
#> 3 1-arachidonoylgly… -1.01 -0.165 -9.63 6.57e-18 4.02e-17 29.7 Lipid
#> 4 1-arachidonylglyc… -0.256 -1.24 -2.03 4.36e- 2 5.79e- 2 -5.62 Lipid
#> 5 1-docosahexaenoyl… -1.13 -0.617 -6.60 4.61e-10 1.50e- 9 11.9 Lipid
#> 6 1-heptadecanoylgl… -1.83 -0.420 -9.22 9.04e-17 5.05e-16 27.1 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>