View source: R/function_visualizations.R
shinyMsQuality function starts a shiny application to
visualize the quality metrics interactively. It allows to display all metrics
The function accepts the output of
The plots within the shiny application can be saved by clicking on the download button.
Thomas Naake, email@example.com
library(msdata) library(MsExperiment) library(S4Vectors) msexp <- MsExperiment() sd <- DataFrame(sample_id = c("QC1", "QC2"), sample_name = c("QC Pool", "QC Pool"), injection_idx = c(1, 3)) sampleData(msexp) <- sd ## define file names containing spectra data for the samples and ## add them, along with other arbitrary files to the experiment fls <- dir(system.file("sciex", package = "msdata"), full.names = TRUE) experimentFiles(msexp) <- MsExperimentFiles( mzML_files = fls, annotations = "internal_standards.txt") ## link samples to data files: first sample to first file in "mzML_files", ## second sample to second file in "mzML_files" msexp <- linkSampleData(msexp, with = "experimentFiles.mzML_files", sampleIndex = c(1, 2), withIndex = c(1, 2)) msexp <- linkSampleData(msexp, with = "experimentFiles.annotations", sampleIndex = c(1, 2), withIndex = c(1, 1)) library(Spectra) ## import the data and add it to the mse object spectra(msexp) <- Spectra(fls, backend = MsBackendMzR()) ## define the quality metrics to be calculated metrics <- c("areaUnderTic", "rtDuration", "msSignal10xChange") ## calculate the metrics ## additional parameters passed to the quality metrics functions ## (msLevel is an argument of areaUnderTic and msSignal10xChange, ## relativeTo is an argument of msSignal10xChange) qc <- calculateMetricsFromMsExperiment(msexp = msexp, metrics = metrics, msLevel = 1, relativeTo = "Q1", change = "jump") rownames(qc) <- c("Sample 1", "Sample 2") if (interactive()) shinyMsQuality(qc = qc)
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