readProteomeExperiment
reads and processes proteomics data from
multiple samples, applying various quality filters, and returns a
SummarizedExperiment
object.
Arguments
- fileTable
A
data.table
ordata.frame
containing the file information with columns for file names, sample names, and IDs.- fdrCut
A
numeric
value specifying the maximum false discovery rate (FDR) threshold. Default is 0.1.- scoreCut
A
numeric
value specifying the minimum score threshold. Default is 10.- pepNumCut
A
numeric
value specifying the minimum number of peptides required for a protein to be included. Default is 1.- ifLFQ
A
logical
value indicating whether to use LFQ quantification. Default isTRUE
.
Details
This function processes proteomics data by filtering based on FDR, score,
and peptide count, and optionally using LFQ quantification. It aggregates
the data from multiple samples and constructs a SummarizedExperiment
object.
Examples
file1 <- system.file("extdata", "phosDDA_1.xls", package = "SmartPhos")
file2 <- system.file("extdata", "proteomeDDA_1.xls", package = "SmartPhos")
# Create fileTable
fileTable <- data.frame(
searchType = c("phosphoproteome", "proteome"),
fileName = c(file1, file2),
sample = c("Sample1", "sample1"),
id = c("s1", "s2")
)
# Call the function
readProteomeExperiment(fileTable, fdrCut = 0.1, scoreCut = 10,
pepNumCut = 1, ifLFQ = TRUE)
#> class: SummarizedExperiment
#> dim: 2 1
#> metadata(0):
#> assays(1): Intensity
#> rownames(2): p1 p2
#> rowData names(3): UniprotID Gene PeptideCounts
#> colnames(1): s2
#> colData names(0):