Nothing
## ---- include = FALSE---------------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
## ----logs---------------------------------------------------------------------
library(MSstatsConvert)
# default - creates a new file
MSstatsLogsSettings(use_log_file = TRUE, append = FALSE)
# default - creates a new file
MSstatsLogsSettings(use_log_file = TRUE, append = TRUE,
log_file_path = "log_file.log")
# switches logging off
MSstatsLogsSettings(use_log_file = FALSE, append = FALSE)
# switches off logs and messages
MSstatsLogsSettings(use_log_file = FALSE, verbose = FALSE)
## -----------------------------------------------------------------------------
MSstatsSaveSessionInfo()
## -----------------------------------------------------------------------------
maxquant_evidence = read.csv(system.file("tinytest/raw_data/MaxQuant/mq_ev.csv",
package = "MSstatsConvert"))
maxquant_proteins = read.csv(system.file("tinytest/raw_data/MaxQuant/mq_pg.csv",
package = "MSstatsConvert"))
maxquant_imported = MSstatsImport(list(evidence = maxquant_evidence,
protein_groups = maxquant_proteins),
type = "MSstats", tool = "MaxQuant")
is(maxquant_imported)
openms_input = read.csv(system.file(
"tinytest/raw_data/OpenMSTMT/openmstmt_input.csv",
package = "MSstatsConvert"
))
openms_imported = MSstatsImport(list(input = openms_input),
"MSstatsTMT", "OpenMS")
is(openms_imported)
## -----------------------------------------------------------------------------
getInputFile(maxquant_imported, "evidence")[1:5, 1:5]
## -----------------------------------------------------------------------------
maxquant_cleaned = MSstatsClean(maxquant_imported, protein_id_col = "Proteins")
head(maxquant_cleaned)
openms_cleaned = MSstatsClean(openms_imported)
head(openms_cleaned)
## -----------------------------------------------------------------------------
maxquant_annotation = read.csv(system.file(
"tinytest/raw_data/MaxQuant/annotation.csv",
package = "MSstatsConvert"
))
maxquant_annotation = MSstatsMakeAnnotation(maxquant_cleaned,
maxquant_annotation,
Run = "Rawfile")
m_filter = list(col_name = "PeptideSequence",
pattern = "M",
filter = TRUE,
drop_column = FALSE)
oxidation_filter = list(col_name = "Modifications",
pattern = "Oxidation",
filter = TRUE,
drop_column = TRUE)
feature_columns = c("PeptideSequence", "PrecursorCharge")
maxquant_processed = MSstatsPreprocess(
maxquant_cleaned,
maxquant_annotation,
feature_columns,
remove_shared_peptides = TRUE,
remove_single_feature_proteins = FALSE,
pattern_filtering = list(oxidation = oxidation_filter,
m = m_filter),
feature_cleaning = list(remove_features_with_few_measurements = TRUE,
summarize_multiple_psms = max),
columns_to_fill = list("FragmentIon" = NA,
"ProductCharge" = NA,
"IsotopeLabelType" = "L"))
head(maxquant_processed)
# OpenMS - TMT data
feature_columns_tmt = c("PeptideSequence", "PrecursorCharge")
openms_processed = MSstatsPreprocess(
openms_cleaned,
NULL,
feature_columns_tmt,
remove_shared_peptides = TRUE,
remove_single_feature_proteins = TRUE,
feature_cleaning = list(remove_features_with_few_measurements = TRUE,
summarize_multiple_psms = max)
)
head(openms_processed)
## ---- eval = FALSE------------------------------------------------------------
# list(
# list(score_column = "Intensity", score_threshold = 1,
# direction = "greater", behavior = "remove",
# handle_na = "remove", fill_value = NA, filter = TRUE, drop = FALSE
# )
# )
## -----------------------------------------------------------------------------
maxquant_balanced = MSstatsBalancedDesign(maxquant_processed, feature_columns)
head(maxquant_balanced)
dim(maxquant_balanced)
dim(maxquant_processed)
openms_balanced = MSstatsBalancedDesign(openms_processed, feature_columns_tmt)
head(openms_balanced)
dim(openms_balanced)
dim(openms_processed)
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