The data set of Lee et al. (2019) contains metabolite information measured by reverse phase liquid chromatography (RPLC) coupled to mass spectrometry and hydrophilic interaction liquid chromatography (HILIC) coupled to mass spectrometry (file 'STables - rev1.xlsx' in the Supplementary Information). The xlsx sheets 'Methods' and 'Raw data' were stored as txt files.
Lee_2019_meta_vals contains two data frame objects:
one containing information on metabolite meta-data and one containing
intensity values on metabolites.
The object will be used as an example data set in the vignette to
show the functionality of the packages.
Thomas Naake, email@example.com
path_to_meta <- "Lee_et_al_2019_Stables_rev1_Methods.txt" meta <- read.delim(path_to_meta, dec = ".", header = TRUE)
## print number of metabolites per measurement (meta data) table(meta$Method)
path_to_vals <- "Lee_et_al_2019_Stables_rev1_Raw_data.txt" vals <- read.delim(path_to_vals, dec = ".", header = TRUE)
## print number of metabolites per measurement (intensity data) table(grepl(vals$Metabolite, pattern = "_rp$")) table(grepl(vals$Metabolite, pattern = "_hn$"))
## save the two objects as an RData object save(meta, vals, file = "Lee_2019_meta_vals.RData", compress = "xz")
Lee et al. (2019). A large-scale analysis of targeted metabolomics data from heterogeneous biological samples provides insights into metabolite dynamics. Metabolomics, 103, doi: 10.1007/s11306-019-1564-8.
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