Package: CardinalWorkflows 1.44.0

Kylie A. Bemis

CardinalWorkflows: Datasets and workflows for the Cardinal MSI

Datasets and workflows for Cardinal: DESI and MALDI examples including pig fetus, cardinal painting, and human RCC.

Authors:Kylie A. Bemis <[email protected]>

CardinalWorkflows_1.44.0.tar.gz
CardinalWorkflows_1.44.0.tar.gz(r-4.7-any)CardinalWorkflows_1.44.0.tar.gz(r-4.6-any)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
CardinalWorkflows/json (API)

# Install 'CardinalWorkflows' in R:
install.packages('CardinalWorkflows', repos = c('https://bioc-release.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:

On BioConductor:CardinalWorkflows-1.45.0(data/experiment 3.24)CardinalWorkflows-1.44.0(data/experiment 3.23)

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

experimentdatamassspectrometrydataimagingmassspectrometrydatadatapkg

4.48 score 8 scripts 1 exports 23 dependencies

Last updated from:83f5227d60 (on RELEASE_3_23). Checks:1 ERROR, 3 OK. Indexed: no.

TargetResultTimeFilesSyslog
bioc-checksERROR165
linux-develOK332
source / vignettesOK2288
linux-releaseOK295

Exports:exampleMSIData

Dependencies:BHBiobaseBiocGenericsBiocParallelCardinalCardinalIOcodetoolscpp11digestformatRfutile.loggerfutile.optionsgenericsirlbalambda.rlatticeMatrixmatternlmeontologyIndexProtGenericsS4Vectorssnow

Segmentation of MS imaging experiments with Cardinal
Introduction | Segmentation of a pig fetus wholy body cross section | Pre-processing | Visualization | Ion images | Principal components analysis (PCA) | Non-negative matrix factorization (NMF) | Segmentation with spatial shrunken centroids (SSC) | Plotting the segmentation | Plotting the (shrunken) mean spectra | Plotting and interpretting t-statistics of the m/z values | Retrieving the top m/z values | Segmentation of a cardinal painting | Segmentation with SSC | Session information
Rendered fromMSI-segmentation.Rmdusingknitr::rmarkdown

Last update: 2024-09-12
Started: 2019-10-29

Classification of MS imaging experiments with Cardinal
Introduction | Classification of a renal cell carcinoma (RCC) cancer dataset | Pre-processing | Visualization | Ion images | Principal components analysis (PCA) | Non-negative matrix factorization (NMF) | Classification with spatial shrunken centroids (SSC) | Cross-validation with SSC | Plotting the classified images | Plotting the (shrunken) mean spectra | Plotting and interpretting t-statistics of the m/z values | Retrieving the top m/z-values | Multiple instance learning (MIL) | Preparing the samples (bags) | Cross-validation with MIL | Additional notes on cross-validation | Session information
Rendered fromMSI-classification.Rmdusingknitr::rmarkdown

Last update: 2024-09-12
Started: 2019-10-29

Class comparison for MSI experiments with Cardinal
Introduction | Statistical testing for a renal cell carcinoma (RCC) cancer dataset | Pre-processing | Non-specific filtering to reduce data size | Segmentation with spatial Dirichlet Gaussian mixture model (DGMM) | Class comparison with means-based testing | Fitting models with means-summarized groups | Interpreting the results | Class comparison with segmentation-based testing | Fitting models with spatial-DGMM-summarized groups | Session information
Rendered fromMSI-testing.Rmdusingknitr::rmarkdown

Last update: 2024-09-12
Started: 2019-10-29

Readme and manuals

Help Manual

Help pageTopics
Datasets and workflows for the Cardinal mass spectrometry imaging packageCardinalWorkflows-package CardinalWorkflows exampleMSIData
Cardinal Paintingcardinal cardinal.peaklist cardinal.peaks data:cardinal data:cardinal.peaklist data:cardinal.peaks
Cross-Section of a Whole Pig Fetusdata:pig206 data:pig206.peaklist data:pig206.peaks pig206 pig206.peaklist pig206.peaks
Human Renal Cell Carcinomadata:rcc data:rcc.resample data:rcc.small rcc rcc.resample rcc.small