## -------------------------------------------------------------------------- library(specL) ## ----eval=FALSE------------------------------------------------------------ # library(rmarkdown) # library(BiocStyle) # report_file <- tempfile(fileext='.Rmd'); # file.copy(system.file("doc", "report.Rmd", # package = "specL"), # report_file); # rmarkdown::render(report_file, # output_format='html_document', # output_file='/tmp/report_specL.html') ## -------------------------------------------------------------------------- if(!exists("INPUT")){ INPUT <- list(FASTA_FILE = system.file("extdata", "SP201602-specL.fasta.gz", package = "specL"), BLIB_FILTERED_FILE = system.file("extdata", "peptideStd.sqlite", package = "specL"), BLIB_REDUNDANT_FILE = system.file("extdata", "peptideStd_redundant.sqlite", package = "specL"), MIN_IONS = 5, MAX_IONS = 6, MZ_ERROR = 0.05, MASCOTSCORECUTOFF = 17, FRAGMENTIONMZRANGE = c(300, 1250), FRAGMENTIONRANGE = c(5, 200), NORMRTPEPTIDES = specL::iRTpeptides, OUTPUT_LIBRARY_FILE = tempfile(), ANNOTATE = TRUE ) } ## ----echo=FALSE, eval=FALSE------------------------------------------------ # cat( # " MASCOTSCORECUTOFF = ", INPUT$MASCOTSCORECUTOFF, "\n", # " BLIB_FILTERED_FILE = ", INPUT$BLIB_FILTERED_FILE, "\n", # " BLIB_REDUNDANT_FILE = ", INPUT$BLIB_REDUNDANT_FILE, "\n", # " MZ_ERROR = ", INPUT$MZ_ERROR, "\n", # " FRAGMENTIONMZRANGE = ", INPUT$FRAGMENTIONMZRANGE, "\n", # " FRAGMENTIONRANGE = ", INPUT$FRAGMENTIONRANGE, "\n", # " FASTA_FILE = ", INPUT$FASTA_FILE, "\n", # " MAX_IONS = ", INPUT$MAX_IONS, "\n", # " MIN_IONS = ", INPUT$MIN_IONS, "\n" # ) # ## ----echo=FALSE, results='asis'-------------------------------------------- library(knitr) # kable(t(as.data.frame(INPUT))) ii <- ((lapply(INPUT, function(x){ if(typeof(x) %in% c("character", "double")){paste(x, collapse = ', ')}else{NULL} } ))) parameter <- as.data.frame(unlist(ii)) names(parameter) <- 'parameter.values' kable(parameter, caption = 'used INPUT parameter') ## -------------------------------------------------------------------------- fragmentIonFunction_specL <- function (b, y) { Hydrogen <- 1.007825 Oxygen <- 15.994915 Nitrogen <- 14.003074 b1_ <- (b ) y1_ <- (y ) b2_ <- (b + Hydrogen) / 2 y2_ <- (y + Hydrogen) / 2 return( cbind(b1_, y1_, b2_, y2_) ) } ## ----warning=FALSE--------------------------------------------------------- BLIB_FILTERED <- read.bibliospec(INPUT$BLIB_FILTERED_FILE) summary(BLIB_FILTERED) ## ----warning=FALSE--------------------------------------------------------- BLIB_REDUNDANT <- read.bibliospec(INPUT$BLIB_REDUNDANT_FILE) summary(BLIB_REDUNDANT) ## ----read.fasta------------------------------------------------------------ if(INPUT$ANNOTATE){ FASTA <- read.fasta(INPUT$FASTA_FILE, seqtype = "AA", as.string = TRUE) BLIB_FILTERED <- annotate.protein_id(BLIB_FILTERED, fasta = FASTA) } ## ----checkIRTs, echo=FALSE, results='asis'--------------------------------- library(knitr) incl <- INPUT$NORMRTPEPTIDES$peptide %in% sapply(BLIB_REDUNDANT, function(x){x$peptideSequence}) INPUT$NORMRTPEPTIDES$included <- incl if (sum(incl) > 0){ res <- INPUT$NORMRTPEPTIDES[order(INPUT$NORMRTPEPTIDES$rt),] # row.names(res) <- 1:nrow(res) kable(res, caption='peptides used for RT normaization.') } ## ----specL::genSwathIonLib, message=FALSE---------------------------------- specLibrary <- specL::genSwathIonLib( data = BLIB_FILTERED, data.fit = BLIB_REDUNDANT, max.mZ.Da.error = INPUT$MZ_ERROR, topN = INPUT$MAX_IONS, fragmentIonMzRange = INPUT$FRAGMENTIONMZRANGE, fragmentIonRange = INPUT$FRAGMENTIONRANGE, fragmentIonFUN = fragmentIonFunction_specL, mascotIonScoreCutOFF = INPUT$MASCOTSCORECUTOFF, iRT = INPUT$NORMRTPEPTIDES ) ## ----summary--------------------------------------------------------------- summary(specLibrary) ## -------------------------------------------------------------------------- # slotNames(specLibrary@ionlibrary[[1]]) specLibrary@ionlibrary[[1]] ## ----fig.retina=3---------------------------------------------------------- plot(specLibrary@ionlibrary[[1]]) ## ----fig.retina=3---------------------------------------------------------- plot(specLibrary) ## ----write.spectronaut, eval=TRUE------------------------------------------ write.spectronaut(specLibrary, file = INPUT$OUTPUT_LIBRARY_FILE) ## ----sessionInfo, echo=FALSE----------------------------------------------- sessionInfo()