Load real-world proteomics data into a SummarizedExperiment
Usage
load_data(
data,
md,
protein_column = "Protein.IDs",
gene_column = "Gene.Names",
ref_samples = NULL,
batch_column = NULL,
condition_column = NULL,
label_column = NULL
)
Arguments
- data
tabular data table with rows = proteins and columns = samples (such as proteinGroups.txt of MaxQuant)
- md
experimental design table (requires a column named "Column" for the column names of the sample intensities in data)
- protein_column
name of the column in data containing the protein IDs
- gene_column
name of the column in data containing the gene names
- ref_samples
reference samples if TMT experiment provided (names of samples)
- batch_column
name of the column in md defining the batches
- condition_column
name of the column in md defining the condition (can still be changed afterwards)
- label_column
name of the column in md containing simple sample names (for visualization)
Examples
data_path <- readPRONE_example("tuberculosis_protein_intensities.csv")
md_path <- readPRONE_example("tuberculosis_metadata.csv")
data <- read.csv(data_path)
md <- read.csv(md_path)
md$Column <- stringr::str_replace_all(md$Column, " ", ".")
ref_samples <- md[md$Group == "ref",]$Column
se <- load_data(data, md, protein_column = "Protein.IDs",
gene_column = "Gene.names", ref_samples = ref_samples,
batch_column = "Pool", condition_column = "Group",
label_column = "Label")