MSstatsQCgui
translates the modern methods of
longitudinal statistical process control, such as simultaneous and time
weighted control charts and change point analysis to the context of
LC-MS experiments. Details can be found via MSstatsQC website and project github repository,
and are available for use stand-alone, or for integration with automated
pipelines.
This vignette summarizes functionalities in MSstatsQCgui
package.
The GUI was created using Shiny, a Web Application Framework for R, and uses several packages to provide advanced features that can enhance Shiny apps, such as shinyjs. A running version of the GUI is found in MSstatsQCgui
To install the package from the Bioconductor repository please use the following code.
if (!requireNamespace("BiocManager", quietly=TRUE))
install.packages("BiocManager")
BiocManager::install("MSstatsQCgui")
To install the development version of the package via GitHub:
The following commands should be used to start the graphical user interface.
In order to analyze quality control data in
MSstatsQCgui
, input data must be a .csv file in a “long”
format with related columns. This is a common data format that can be
generated from spectral processing tools such as Skyline and Panorama
AutoQC.
The recommended format includes Acquired Time
,
Peptide name
, Annotations
and data for any QC
metrics such as Retention Time
,
Total Peak Area
and Mass Accuracy
etc. Each
input file should include Acquired Time
,
Peptide name
and Annotations
. After the
Annotations
column user can parse any metric of interest
with a proper column name. MSstatsQCgui
can analyze 20
metrics simultaneously.
AcquiredTime
: This column shows the acquired time of
the QC/SST sample in the format of MM/DD/YYYY HH:MM:SS AM/PM. European
date parser is also accepted.
Precursor
: This column shows information about
Precursor id. Statistical analysis will be done separately for each
unique label in this column.
Annotations
: Annotations are free-text information
given by the analyst about each run. They can be informative
explanations of any special cause or any observations related to a
particular run. Annotations are carried in the plots provided by
MSstatsQC
interactively.
(d)-(f) RetentionTime
, TotalPeakArea
,
FWHM
, MassAccuracy
, and
PeakAssymetry
, and other metrics: These columns define a
feature of a peak for a specific peptide.
Example dataset was generated during CPTAC Study 9.1 at Site 54. Although the example focus on targeted proteomics, the statistical methods more generally apply. Each row corresponds to a single time point.
Data import
tab is used to import data. User can also
run the app with sample data and clear the outputs with the clear
button.
Run with sample data
: Click to run MSstatsQC with
sample data from CPTAC Study 9.1.Clear data and plots
: Click to clear all data and
plots.See Input Example
Data import
tab automatically checks data and validate
it for further use.
Options
tab is used to set metrics and peptides of
interest. Guide set and known mean and standard deviation are also set
within “Options” tab. User should select a proper and representative
guide set using Options
tab. The lower bound of guide set
indicates the index of the first time point to be included in the guide
set. For example, if you choose “1” as a lower bound, it means that
first time point will be the first element of the guide set. Similarly,
upper bound of guide set shows the index for the last observation. It is
possible to use different guide sets for different metrics and
peptides.
Control charts
tab is used to construct X and mR and
CUSUMm and CUSUMv control charts.
See XmR Chart Tab
Summary plots are available in the Metric summary
tab
under Detailed performance: plot summaries
.
Plots created by the core plot functions are generated by plotly which is an R package for interactive plot generation. Each output generated by ‘plotly’ can be saved using the “plotly” toolset.
Please use MSstats.org/MSstatsQC and github repository for further details about this tool.
Please use Google group if you want to file bug reports or feature requests.
Please cite MSstatsQCGUI:
## R Under development (unstable) (2024-10-21 r87258)
## Platform: x86_64-pc-linux-gnu
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## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
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## [1] digest_0.6.37 R6_2.5.1 fastmap_1.2.0 xfun_0.48
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