An object of class
Biobase::ExpressionSet
containing log\(_2\)-transformed metabolite data for differential
analysis and WGCNA.
METAB_EXPObject of class
Biobase::ExpressionSet with 1063
features and 50 samples.
Fahy, E., & Subramaniam, S. (2020). RefMet: A reference nomenclature for metabolomics. Nature Methods, 17(12), 1173–1174. https://doi.org/10.1038/s41592-020-01009-y
library(Biobase)
#> Loading required package: BiocGenerics
#>
#> Attaching package: ‘BiocGenerics’
#> The following objects are masked from ‘package:stats’:
#>
#> IQR, mad, sd, var, xtabs
#> The following objects are masked from ‘package:base’:
#>
#> Filter, Find, Map, Position, Reduce, anyDuplicated, aperm, append,
#> as.data.frame, basename, cbind, colnames, dirname, do.call,
#> duplicated, eval, evalq, get, grep, grepl, intersect, is.unsorted,
#> lapply, mapply, match, mget, order, paste, pmax, pmax.int, pmin,
#> pmin.int, rank, rbind, rownames, sapply, setdiff, table, tapply,
#> union, unique, unsplit, which.max, which.min
#> Welcome to Bioconductor
#>
#> Vignettes contain introductory material; view with
#> 'browseVignettes()'. To cite Bioconductor, see
#> 'citation("Biobase")', and for packages 'citation("pkgname")'.
METAB_EXP # summary
#> ExpressionSet (storageMode: lockedEnvironment)
#> assayData: 1063 features, 50 samples
#> element names: exprs
#> protocolData: none
#> phenoData
#> sampleNames: 10043527 10043950 ... 10026193 (50 total)
#> varLabels: pid bid ... exp_group (6 total)
#> varMetadata: labelDescription
#> featureData
#> featureNames: 3-methyl-2-oxovalerate 5'-methylthioadenosine ...
#> sedoheptulose-7-phosphate (1063 total)
#> fvarLabels: feature_ID dataset ... formula (13 total)
#> fvarMetadata: labelDescription
#> experimentData: use 'experimentData(object)'
#> Annotation:
exprs(METAB_EXP)[1:10, 1:5] # assayData (first 10 rows and 5 columns)
#> 10043527 10043950 10044337 10046119 10046380
#> 3-methyl-2-oxovalerate 1.178894 0.9060579 0.008567142 -0.8926003 0.4339056
#> 5'-methylthioadenosine -3.528231 -4.2752777 -7.236768016 -6.3275334 -4.1024668
#> adenosine 4.437239 4.1397055 4.679195002 4.1583898 4.5390403
#> ADP 3.410435 3.0386412 4.437419080 3.9750911 3.9017748
#> Alanine NA -0.4870398 -0.179877286 -0.4590593 -0.3163109
#> AMP 2.528949 0.9225197 2.897239407 2.4056311 2.6180835
#> Anserine NA -7.1303497 -0.209715023 -1.5475741 -2.5877989
#> Arginine NA -2.3855330 -2.218783654 -2.5437574 -1.6949176
#> Asparagine NA -2.4311125 -1.990426951 -2.3243017 -1.8801836
#> Aspartic Acid NA -2.2169214 -2.077245870 -1.5561938 -1.6443759
head(fData(METAB_EXP)) # featureData
#> feature_ID dataset
#> 3-methyl-2-oxovalerate 3-methyl-2-oxovalerate metab-t-ka
#> 5'-methylthioadenosine 5'-methylthioadenosine metab-t-nuc
#> adenosine adenosine metab-u-hilicpos
#> ADP ADP metab-t-nuc
#> Alanine Alanine metab-t-amines
#> AMP AMP metab-t-nuc
#> name_in_figures refmet_super_class
#> 3-methyl-2-oxovalerate 3-Methyl-2-oxovaleric acid Organic acids
#> 5'-methylthioadenosine 5'-Methylthioadenosine Nucleic acids
#> adenosine Adenosine Nucleic acids
#> ADP ADP Nucleic acids
#> Alanine Alanine Organic acids
#> AMP AMP Nucleic acids
#> refmet_main_class refmet_sub_class
#> 3-methyl-2-oxovalerate Keto acids Short-chain keto acids
#> 5'-methylthioadenosine Purines Purine ribonucleosides
#> adenosine Purines Purine ribonucleosides
#> ADP Purines Purine rNDP
#> Alanine Amino acids and peptides Amino acids
#> AMP Purines Purine rNMP
#> lipid_class chain_length double_bond rt mz
#> 3-methyl-2-oxovalerate <NA> NA NA 0.00 0.0000
#> 5'-methylthioadenosine <NA> NA NA 0.00 0.0000
#> adenosine <NA> NA NA 5.03 268.1034
#> ADP <NA> NA NA 0.00 0.0000
#> Alanine <NA> NA NA 13.30 260.3000
#> AMP <NA> NA NA 0.00 0.0000
#> neutral_mass formula
#> 3-methyl-2-oxovalerate 130.0630 C6H10O3
#> 5'-methylthioadenosine 297.0896 C11H15N5O3S
#> adenosine 267.0968 C10H13N5O4
#> ADP 427.0294 C10H15N5O10P2
#> Alanine 89.0477 C3H7NO2
#> AMP 347.0631 C10H14N5O7P
head(pData(METAB_EXP)) # phenoData
#> pid bid viallabel sex timepoint exp_group
#> 10043527 10043527 90245 90245017009 Female SED F_SED
#> 10043950 10043950 90248 90248017009 Female SED F_SED
#> 10044337 10044337 90252 90252017009 Female SED F_SED
#> 10046119 10046119 90265 90265017009 Female SED F_SED
#> 10046380 10046380 90266 90266017009 Female SED F_SED
#> 10700102 10700102 90560 90560017009 Female 1W F_1W