MSstatsClean | R Documentation |
Clean files generated by a signal processing tools.
Clean DIAUmpire files
Clean MaxQuant files
Clean OpenMS files
Clean OpenSWATH files
Clean Progenesis files
Clean ProteomeDiscoverer files
Clean Skyline files
Clean SpectroMine files
Clean Spectronaut files
Clean Philosopher files
Clean DIA-NN files
Clean Metamorpheus files
Clean Protein Prospector files
MSstatsClean(msstats_object, ...)
## S4 method for signature 'MSstatsDIAUmpireFiles'
MSstatsClean(msstats_object, use_frag, use_pept)
## S4 method for signature 'MSstatsMaxQuantFiles'
MSstatsClean(
msstats_object,
protein_id_col,
remove_by_site = FALSE,
channel_columns = "Reporterintensitycorrected"
)
## S4 method for signature 'MSstatsOpenMSFiles'
MSstatsClean(msstats_object)
## S4 method for signature 'MSstatsOpenSWATHFiles'
MSstatsClean(msstats_object)
## S4 method for signature 'MSstatsProgenesisFiles'
MSstatsClean(msstats_object, runs, fix_colnames = TRUE)
## S4 method for signature 'MSstatsProteomeDiscovererFiles'
MSstatsClean(
msstats_object,
quantification_column,
protein_id_column,
sequence_column,
remove_shared,
remove_protein_groups = TRUE,
intensity_columns_regexp = "Abundance"
)
## S4 method for signature 'MSstatsSkylineFiles'
MSstatsClean(msstats_object)
## S4 method for signature 'MSstatsSpectroMineFiles'
MSstatsClean(msstats_object)
## S4 method for signature 'MSstatsSpectronautFiles'
MSstatsClean(msstats_object, intensity)
## S4 method for signature 'MSstatsPhilosopherFiles'
MSstatsClean(
msstats_object,
protein_id_col,
peptide_id_col,
channels,
remove_shared_peptides
)
## S4 method for signature 'MSstatsDIANNFiles'
MSstatsClean(
msstats_object,
MBR = TRUE,
quantificationColumn = "FragmentQuantCorrected"
)
## S4 method for signature 'MSstatsMetamorpheusFiles'
MSstatsClean(msstats_object)
## S4 method for signature 'MSstatsProteinProspectorFiles'
MSstatsClean(msstats_object)
msstats_object |
object that inherits from |
... |
additional parameter to specific cleaning functions. |
use_frag |
TRUE will use the selected fragment for each peptide. 'Selected_fragments' column is required. |
use_pept |
TRUE will use the selected fragment for each protein 'Selected_peptides' column is required. |
protein_id_col |
character, name of a column with names of proteins. |
remove_by_site |
logical, if TRUE, proteins only identified by site will be removed. |
channel_columns |
character, regular expression that identifies channel columns in TMT data. |
runs |
chr, vector of Run labels. |
fix_colnames |
lgl, if TRUE, one of the rows will be used as colnames. |
quantification_column |
chr, name of a column used for quantification. |
protein_id_column |
chr, name of a column with protein IDs. |
sequence_column |
chr, name of a column with peptide sequences. |
remove_shared |
lgl, if TRUE, shared peptides will be removed. |
remove_protein_groups |
if TRUE, proteins with numProteins > 1 will be removed. |
intensity_columns_regexp |
regular expressions that defines intensity columns. Defaults to "Abundance", which means that columns that contain the word "Abundance" will be treated as corresponding to intensities for different channels. |
intensity |
chr, specifies which column will be used for Intensity. |
peptide_id_col |
character name of a column that identifies peptides |
channels |
character vector of channel labels |
remove_shared_peptides |
logical, if TRUE, shared peptides will be removed based on the IsUnique column from Philosopher output |
MBR |
True if analysis was done with match between runs |
quantificationColumn |
Use 'FragmentQuantCorrected'(default) column for quantified intensities. 'FragmentQuantRaw' can be used instead. |
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evidence_path = system.file("tinytest/raw_data/MaxQuant/mq_ev.csv",
package = "MSstatsConvert")
pg_path = system.file("tinytest/raw_data/MaxQuant/mq_pg.csv",
package = "MSstatsConvert")
evidence = read.csv(evidence_path)
pg = read.csv(pg_path)
imported = MSstatsImport(list(evidence = evidence, protein_groups = pg),
"MSstats", "MaxQuant")
cleaned_data = MSstatsClean(imported, protein_id_col = "Proteins")
head(cleaned_data)
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