# CREATE SAMPLE DATA FILES FOR THE PACKAGE----
setwd('~/github/biodavidjm/artMS/')
# CONFIGURATION FILE----
# library(yaml)
artms_config <- yaml.load_file("~/github/biodavidjm/artMS/inst/extdata/artms_config.yaml")
save(artms_config, file = '~/github/biodavidjm/artMS/data/artms_config.RData', compress = TRUE)
# GENERATE RANDOM FILE----
artms_data_randomDF <- data.frame(replicate(10, sample(0:1, 100, rep = TRUE)))
save(artms_data_randomDF, file = 'data/artms_data_randomDF.RData',
compress = 'xz')
## CREATE THE OFFICIAL PHGLOBAL COMING WITH THE PACKAGE-----
setwd("~/sourcecode/artms/ph_full/")
evidence_file <- 'evidence.txt'
keys_file <- 'keys.txt'
contrast_file <- 'contrast.txt'
edf <- read.delim(evidence_file,
stringsAsFactors = FALSE)
kdf <- read.delim(keys_file,
stringsAsFactors = FALSE,
check.names = FALSE)
# Select 2 biological replicates
selectedBR <- c("qx006145", "qx006148", "qx006151", "qx006152")
edfnew <- edf[which(edf$Raw.file %in% selectedBR), ]
# Select columns
edfnew <- edfnew[c("Sequence",
"Length",
"Modifications",
"Modified.sequence",
"Oxidation..M..Probabilities",
"Phospho..STY..Probabilities",
"Oxidation..M..Score.Diffs",
"Phospho..STY..Score.Diffs",
"Oxidation..M.",
"Phospho..STY.",
"Missed.cleavages",
"Proteins",
"Leading.proteins",
"Leading.razor.protein",
"Type",
"Raw.file",
"MS.MS.m.z",
"Charge",
"m.z",
"Mass",
"Resolution",
"Mass.error..ppm.",
"Mass.error..Da.",
"Uncalibrated.mass.error..ppm.",
"Uncalibrated.mass.error..Da.",
"Calibrated.retention.time",
"Retention.time",
"Retention.length",
"PEP",
"MS.MS.count",
"MS.MS.scan.number",
"Score",
"Delta.score",
"Intensity",
"Reverse",
"Potential.contaminant")]
artms_data_ph_keys <- kdf[which(kdf$RawFile %in% selectedBR),]
# And random sampling lines
n <- round(dim(edfnew)[1] / 25)
artms_data_ph_evidence <- edfnew[sample(nrow(edfnew), n),]
# # print out evidence & keys
# write.table(
# artms_data_ph_evidence,
# file = "~/sourcecode/artms/ph/artms_data_ph_evidence.txt",
# quote = FALSE,
# sep = "\t",
# row.names = FALSE,
# col.names = TRUE
# )
# write.table(
# artms_data_ph_keys,
# file = "~/sourcecode/artms/ph/artms_data_ph_keys.txt",
# quote = FALSE,
# sep = "\t",
# row.names = FALSE,
# col.names = TRUE
# )
# artms_data_ph_evidence----
# artms_data_ph_evidence <- read.delim("~/sourcecode/artms/ph/artms_data_ph_evidence.txt", stringsAsFactors = FALSE)
save(artms_data_ph_evidence,
file = '~/github/biodavidjm/artMS/data/artms_data_ph_evidence.RData',
compress = TRUE)
# artms_data_ph_keys----
# artms_data_ph_keys <- read.delim("~/sourcecode/artms/extdata/artms_data_ph_keys.txt",
# stringsAsFactors = FALSE)
save(artms_data_ph_keys,
file = '~/github/biodavidjm/artMS/data/artms_data_ph_keys.RData',
compress = TRUE )
# artms_data_ph_contrast -----
contrast_file <- "~/sourcecode/artms/ph_full/contrast.txt"
artms_data_ph_contrast <- readLines(contrast_file, warn = FALSE)
save(artms_data_ph_contrast,
file = "~/github/biodavidjm/artMS/data/artms_data_ph_contrast.RData")
# artms_data_ph_config ----
artms_data_ph_config <- artms_config
artms_data_ph_config$files$evidence <- ""
artms_data_ph_config$files$keys <- ""
artms_data_ph_config$files$contrasts <- ""
artms_data_ph_config$files$summary <- ""
artms_data_ph_config$files$output <- "quant-test/results.txt"
artms_data_ph_config$qc$basic <- 0
artms_data_ph_config$qc$extended <- 0
artms_data_ph_config$qc$extendedSummary <- 0
artms_data_ph_config$data$filters$modifications <- "PH"
save(artms_data_ph_config,
file = "~/github/biodavidjm/artMS/data/artms_data_ph_config.RData",
compress = TRUE)
artms_data_ph_config$files$evidence <- artms_data_ph_evidence
artms_data_ph_config$files$keys <- artms_data_ph_keys
artms_data_ph_config$files$contrasts <- artms_data_ph_contrast
artms_data_ph_config$output_extras <- 0
artms_data_ph_config$msstats$profilePlots <- "before, after"
msresults <- artmsQuantification(yaml_config_file = artms_data_ph_config,
data_object = TRUE,
display_msstats = FALSE,
verbose = TRUE,
printPDF = FALSE,
printTables = FALSE)
# Results -----
# Run MSstats on the full version (4 biological replicates)-----
setwd("~/sourcecode/artms/ph_full/")
artmsWriteConfigYamlFile(config_file_name = "artms_full_phglobal.yaml")
artmsQuantification(yaml_config_file = "artms_full_phglobal.yaml")
# Load and write out data objects for artMS
artms_data_ph_msstats_modelqc <- read.delim("~/sourcecode/artms/ph_full/phglobal/new2021/results_ModelQC.txt", stringsAsFactors = FALSE)
save(artms_data_ph_msstats_modelqc,
file = "~/github/biodavidjm/artMS/data/artms_data_ph_msstats_modelqc.RData",
compress = TRUE)
artms_data_ph_msstats_results <-read.delim("~/sourcecode/artms/ph_full/phglobal/new2021/results.txt", stringsAsFactors = FALSE)
save(artms_data_ph_msstats_results,
file = "~/github/biodavidjm/artMS/data/artms_data_ph_msstats_results.RData",
compress = TRUE)
# Using the full version to generate the results file
# To generate results first run:
artms_data_ph_config$files$evidence <- artms_data_ph_evidence
artms_data_ph_config$files$keys <- artms_data_ph_keys
artms_data_ph_config$files$contrasts <- artms_data_ph_contrast
artms_data_ph_quantifications <- artmsQuantification(yaml_config_file = artms_data_ph_config,
data_object = TRUE,
printPDF = TRUE,
display_msstats = TRUE,
verbose = TRUE)
artms_data_ph_msstats_results <- as.data.frame(artms_data_ph_quantifications$ComparisonResult)
artms_data_ph_msstats_results$Protein <- as.character(artms_data_ph_msstats_results$Protein)
artms_data_ph_msstats_results$Label <- as.character(artms_data_ph_msstats_results$Label)
artms_data_ph_msstats_results$issue <- as.character(artms_data_ph_msstats_results$issue)
artms_data_ph_msstats_modelqc <- as.data.frame(artms_data_ph_quantifications$ModelQC)
artms_data_ph_msstats_modelqc$RUN <- as.integer(artms_data_ph_msstats_modelqc$RUN)
artms_data_ph_msstats_modelqc$Protein <- as.character(artms_data_ph_msstats_modelqc$Protein)
artms_data_ph_msstats_modelqc$originalRUN <- as.integer(artms_data_ph_msstats_modelqc$originalRUN)
artms_data_ph_msstats_modelqc$GROUP <- as.character(artms_data_ph_msstats_modelqc$GROUP)
artms_data_ph_msstats_modelqc$SUBJECT <- as.character(artms_data_ph_msstats_modelqc$SUBJECT)
save(artms_data_ph_msstats_results,
file = "~/github/biodavidjm/artMS/data/artms_data_ph_msstats_results2.RData",
compress = TRUE)
save(artms_data_ph_msstats_modelqc,
file = "~/github/biodavidjm/artMS/data/artms_data_ph_msstats_modelqc2.RData",
compress = TRUE)
# CORUM dataset----
artms_data_corum_mito_database <- read.delim("~/github/biodavidjm/artMS/inst/extdata/20170801_corum_mitoT.txt",
stringsAsFactors = FALSE)
save(artms_data_corum_mito_database,
file = 'data/artms_data_corum_mito_database.RData',
compress = TRUE)
# PATHOGENS----
message("--- PATHOGEN IN SAMPLES: TB\n")
artms_data_pathogen_TB <- read.delim('~/Box Sync/db/uniprot/uniprot-tr-myctb_tuberculosis_ATCC35801_TMC10-onlyEntryID.fasta',
header = FALSE,
sep = "\t",
quote = "",
stringsAsFactors = FALSE) # pathogen.ids$Entry, "TB",
names(artms_data_pathogen_TB) <- c('Entry')
save(artms_data_pathogen_TB,
file = '~/github/biodavidjm/artMS/data/artms_data_pathogen_TB.RData',
compress = 'xz')
message("--- PATHOGEN IN SAMPLES: LEGIONELLA PNEUMOPHILA")
artms_data_pathogen_LPN <-
read.delim(
'~/Box Sync/db/uniprot/uniprot-legionella-proteome_UP000000609.txt',
header = TRUE,
sep = "\t",
quote = "",
stringsAsFactors = FALSE
) # pathogen.ids$Entry, "Lpn",
artms_data_pathogen_LPN <- artms_data_pathogen_LPN[c('Entry')]
save(artms_data_pathogen_LPN,
file = '~/github/biodavidjm/artMS/data/artms_data_pathogen_LPN.RData',
compress = 'xz')
# VIGNETTES
artmsQualityControlEvidenceBasic(evidence_file = artms_data_ph_evidence,
keys_file = artms_data_ph_keys,
prot_exp = "PH")
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