Links filtered MS/MS IDs with reporter intensities. Divides reporter ion intensities by corresponding reference and then returns cross-tab. Rows are species (e.g. proteins in global, phosphopeptides in phosphoproteomic experiment), columns are sample names.
Usage
create_crosstab(
msnid,
reporter_intensities,
aggregation_level,
fractions,
samples,
references
)Arguments
- msnid
(MSnID object) filtered MS/MS identifications
- reporter_intensities
(object coercible to data.table) collated table with filtered reporter intensities.
- aggregation_level
(character) defines what intensities needs to be aggregated. At this point the only aggregation function is `sum`. Typically, intensities from different fractions of the same plex are aggregated. Also (e.g. in global proteomics) intensities from different scans identifying peptides from the same protein aggregated together too.
- fractions
(object coercible to data.table) the fractions study design table with Dataset and PlexID columns.
- samples
(object coercible to data.table) the samples study design table with columns PlexID, QuantBlock, ReporterName, ReporterAlias, and MeasurementName.
- references
(object coercible to data.table) the references study design table with columns for PlexID, QuantBlock, and Reference.
Value
(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.
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")
out <- create_crosstab(msnid, masic_data, aggregation_level,
fractions, samples, references)
dim(out)
head(out)
}