Creates MSnSet object from quantitative crosstab and attached phenotype data.
Arguments
- crosstab
(matrix) with log2-transformed relative reporter ion intensities. Row names are the names of the measured species. Column names are the names of the samples.
- samples
(data.table or data.frame) matches sample names to reporter ions.
Value
MSnSet object with log2-transformed relative reporter ion intensities as expression data and the samples table as phenotype data.
Examples
if (FALSE) {
# Prepare MS/MS IDs
path_to_MSGF_results <- system.file("extdata/global/msgf_output",
package = "PlexedPiperTestData")
msnid <- read_msgf_data(path_to_MSGF_results)
msnid <- MSnID::correct_peak_selection(msnid)
show(msnid)
msnid <- filter_msgf_data_peptide_level(msnid, 0.01)
show(msnid)
path_to_FASTA <- system.file(
"extdata/Rattus_norvegicus_NCBI_RefSeq_2018-04-10.fasta.gz",
package = "PlexedPiperTestData"
)
msnid <- compute_num_peptides_per_1000aa(msnid, path_to_FASTA)
msnid <- filter_msgf_data_protein_level(msnid, 0.01)
show(msnid)
# Prepare table with reporter ion intensities
path_to_MASIC_results <- system.file("extdata/global/masic_output",
package = "PlexedPiperTestData")
masic_data <- read_masic_data(path_to_MASIC_results,
interference_score = TRUE)
masic_data <- filter_masic_data(masic_data, 0.5, 0)
# Creating cross-tab
library(readr)
fractions <- read_tsv(system.file("extdata/study_design/fractions.txt",
package = "PlexedPiperTestData"))
samples <- read_tsv(system.file("extdata/study_design/samples.txt",
package = "PlexedPiperTestData"))
references <- read_tsv(system.file("extdata/study_design/references.txt",
package = "PlexedPiperTestData"))
aggregation_level <- c("accession")
crosstab <- create_crosstab(msnid, masic_data, aggregation_level,
fractions, samples, references)
m <- create_msnset(crosstab, samples)
dim(m)
library(MSnbase)
head(exprs(m))
}