MTBLS79: Direct-infusion mass spectrometry (DIMS) data set

MTBLS79R Documentation

Direct-infusion mass spectrometry (DIMS) data set

Description

Data set of 20 biological (cow vs sheep) serum samples that were analysed repeatedly, in 8 batches across 7 days.

Usage

MTBLS79

Format

A RangedSummarizedExperiment-class object.
assay(MTBLS79) Peak intensities of the DIMS data set. Contains 172 samples and 2488 features.
colData(MTBLS79) Sample meta data containing 4 columns.
Batch - character(), sample batch name.
Sample_Rep - character(), sample replicate code.
Class - character(), sample class labels.
Class2 - character(), alternative sample class labels grouping together replicate samples.

Details

Code below includes all commands used to generate MTBLS79 object.

library (openxlsx)
library (SummarizedExperiment)

download.file(destfile = "MTBLS79.xlsx", mode="wb",
url = "ftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/ 
   MTBLS79/Dataset07__SFPM.xlsx") 
wb <- openxlsx::loadWorkbook(xlsxFile="MTBLS79.xlsx")

MTBLS79 <- list()

MTBLS79$assay <- openxlsx::readWorkbook(wb, "data", colNames=T, rowNames=T)

# Last row of the peak matrix represent mean intensities across all samples.
MTBLS79$assay <- MTBLS79$assay[-c(nrow(MTBLS79$assay)), ]

# Transpose peak matrix, so that features are in rows and samples in columns.
MTBLS79$assay <- as.matrix(t(MTBLS79$assay))

# Missing values in the input data are stored as 0, replace with NA
MTBLS79$assay[MTBLS79$assay == 0] <- NA

rownames(MTBLS79$assay) <- round(as.numeric(rownames(MTBLS79$assay)), 5)

MTBLS79$colData <- openxlsx::readWorkbook(wb, "meta", colNames=T, rowNames=F)
MTBLS79$colData <- MTBLS79$colData[-c(nrow(MTBLS79$colData)), 1:4]

MTBLS79 <- SummarizedExperiment(assays=list(MTBLS79$assay), 
colData=DataFrame(MTBLS79$colData))

Source

https://www.ebi.ac.uk/metabolights/MTBLS79

References

Kirwan et al, Scientific Data volume 1, Article number: 140012 (2014) https://www.nature.com/articles/sdata201412


computational-metabolomics/pmp documentation built on March 9, 2024, 4:25 p.m.