knitr::read_chunk(system.file("reports", "scripts", "synergise.R", package="synapter"))
inputFiles <- rbind(c("Identification peptide:", basename(obj$IdentPeptideFile), nrow(obj$IdentPeptideData)), c("Quantitation peptide:", basename(obj$QuantPeptideFile), nrow(obj$QuantPeptideData)), c("Quantitation Pep3D:", basename(obj$QuantPep3DFile), nrow(obj$QuantPep3DData)), c("Fasta file:", basename(obj$DbFastaFile), "")) colnames(inputFiles) <- c("", "File name", "Number of features") knitr::kable(inputFiles, align="llr")
parameters <- rbind(c("Master", master), c("Peptide FDR", fdr), c("Protein FPR", fpr), c("Peptide Length", peplen), c("Missed cleavages", missedCleavages), c("Isoleucin equals Leucin", IisL), c("Identification mass tolerance (ppm)", identppm), c("Quantitation mass tolerance (ppm)", quantppm), c("Loess span (RT modelling)", span.rt), c("Filtering unique peptides", as.character(uniquepep))) colnames(parameters) <- c("Parameter name", "Value") knitr::kable(parameters, align="lr")
gridParameters <- rbind(c("Mass tolerance (ppm) start", grid.ppm.from), c("Mass tolerance (ppm) end", grid.ppm.to), c("Mass tolerance (ppm) by", grid.ppm.by), c("Retention time stdev start", grid.nsd.from), c("Retention time stdev end", grid.nsd.to), c("Retention time stdev by", grid.nsd.by), c("Feature proportion ", grid.subset), c("Number of features", grid.n), c("parameters selection", grid.param.sel)) colnames(gridParameters) <- c("Grid parameter", "Value") knitr::kable(gridParameters, align="lr")
plotFeatures(obj, what="all")
r if(grid.n) { paste0("Using", grid.n, "features.") } else { paste0("Using ",
grid.subset * 100, "% of the data.") }
# abuse inline r here to show the progress bar of the gridsearch in the # R console - regular r chunks capture stdout
r if (grid.n) { searchGrid(obj, ppms=seq(grid.ppm.from, grid.ppm.to, grid.ppm.by), nsds=seq(grid.nsd.from, grid.nsd.to, grid.nsd.by), imdiffs=Inf, n=grid.n, verbose=verbose) } else { searchGrid(obj, ppms=seq(grid.ppm.from, grid.ppm.to, grid.ppm.by), nsds=seq(grid.nsd.from, grid.nsd.to, grid.nsd.by), imdiffs=Inf, subset=grid.subset, verbose=verbose) }
plotGrid(obj, what="details")
names <- c("total", "model", "details") what <- c("total", "model", "details") for (i in seq(along=names)){ cat("\n####", names[i], "\n") cat("\n##### Image\n") plotGrid(obj, what=what[i]) cat("\n\n##### Table\n") print(knitr::kable(as.data.frame(getGrid(obj)[[i]][,,1]))) cat("\nBest Grid Value ", names[i], ": ", getBestGridValue(obj)[i], "\n", sep="") #cat("\n##### Best Grid Parameters\n") print(knitr::kable(as.data.frame(getBestGridParams(obj)[[i]]))) }
gridDetails <- do.call(rbind, getGridDetails(obj)) cond <- do.call(rbind, strsplit(rownames(gridDetails), ":"))[, 1:2] ## imdiff not supported by synergise1 colnames(cond) <- c("nsd", "ppm") gridDetails <- cbind(cond, gridDetails) gridDetails[] <- as.numeric(gridDetails) rownames(gridDetails) <- NULL knitr::kable(as.data.frame(gridDetails))
Setting best grid parameters using 'r grid.param.sel
'
r obj$PpmError
r obj$RtNsd
findEMRTs(obj) rescueEMRTs(obj, mergedEMRTs) plotEMRTtable(obj)
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