Metabolomics workbench project PR001418, study ST002224 where we performed differential metabolite analysis comparing intracellular metabolomics of 786-M1A versus HK2 cells. metabolite values used as input with row names being metabolitetrivial names. nitrogen supports renal cancer progression , Nature Communications 2022, doi:10.1038/s41467-022-35036-4
Format
An object of class spec_tbl_df (inherits from tbl_df, tbl, data.frame) with 179 rows and 14 columns.
Examples
data(intracell_dma)
head(intracell_dma)
#> # A tibble: 6 × 14
#> Metabolite Log2FC p.adj t.val HMDB KEGG.ID KEGGCompound Pathway
#> <chr> <dbl> <dbl> <dbl> <chr> <chr> <chr> <chr>
#> 1 2-aminoadipic acid 0.153 2.38e-1 -7.56e5 HMDB… NA NA Not as…
#> 2 2-hydroxyglutarate 0.932 6.45e-5 -2.02e8 HMDB… C02630 2-Hydroxygl… Citrat…
#> 3 2-ketoglutarate 1.35 7.00e-6 -5.96e8 HMDB… C00026 2-Oxoglutar… Citrat…
#> 4 2/3-phosphoglycerate 0.699 9.46e-4 -1.93e7 HMDB… C00197 3-Phospho-D… Glycol…
#> 5 4-guanidinobutanoate -1.15 1.71e-4 2.37e6 HMDB… C01035 4-Guanidino… Argini…
#> 6 4-hydroxyphenyllact… -0.916 6.17e-8 1.91e6 HMDB… C03672 3-(4-Hydrox… Not as…
#> # ℹ 6 more variables: `786-M1A_1` <dbl>, `786-M1A_2` <dbl>, `786-M1A_3` <dbl>,
#> # HK2_1 <dbl>, HK2_2 <dbl>, HK2_3 <dbl>