OPTION:FORMAT:data format: ' csv_kegg '
OPTION:MISSING:treat LOD/out of quant. data as missing: ' n '
OPTION:OUTLIER:drop outliers : ' n '
OPTION:REFERENCE:drop reference samples : ' n '
OPTION:DEL_METABS:drop metabolites with cv > 0.25 : ' n '
OPTION:RATIOS:calculate metabolite ratios : ' n '
AUX:Barplots of each metabolite class have equal y axis: TRUE 
Read CSV dataset with 190 columns and 48 rows
Data format:  csv_kegg 
EXTRACT: 48  samples and  189  metabolites extracted
PHENOTYPES_UPLOAD:Found  48  matched lines with  4  phenotypes specified<br>
PHENOTYPES_UPLOAD:Ignored  CLIENT_ID  column as each sample has its own phenotype specification while being non-numeric<br>
PHENOTYPES_UPLOAD:Found  DAY DOSE_MG_KG WEIGHT_MG as non-data quality phenotypes<br>
REPLICATES:No replicates
BATCHES:No batches
Wrote machted dataset to data_all_beforeCheck.csv
No replicates in data
No extreme outliers identified
No extreme outliers identified
 48  samples and  189  metabolites in checked data set
Wrote machted dataset to data_all.csv
Phenotype  DAY  is nominal
Phenotype  DOSE_MG_KG  is numeric
Phenotype  DOSE_MG_KG  added to nominal phenotypes also
Phenotype  WEIGHT_MG  is numeric
 Wrote summary.csv file
 189 Distribution plots generated