Introduction | Quick start | Data formats | The provided toy dataset | Reading in data | Load images | Add metadata | Scale images | Add channel names | Generating the SingleCellExperiment object | The CytoImageList object | Accessors | Getting and setting images | Getting and setting channels | Naming and merging channels | Looping | Plotting pixel information | Normalization | Colouring | Adjusting brightness, contrast and gamma | Outlining | Subsetting | Adjusting the colour | Plotting cell information | Changing the assay slot | Outlining | Subsetting | Adjusting the colour | Customisation | Subsetting the SingleCellExperiment object | Background and missing colour | Scale bar and image title | Legend | Setting the margin between images | Scale the feature counts | Image interpolation | Thick borders | Returning plots and images | Integration with ggplot2 objects | Saving images | Gating cells on images | Acknowledgements | Contributions | Session info | References
Package: cytomapper 1.25.0
Lasse Meyer
cytomapper: Visualization of highly multiplexed imaging data in R
Highly multiplexed imaging acquires the single-cell expression of selected proteins in a spatially-resolved fashion. These measurements can be visualised across multiple length-scales. First, pixel-level intensities represent the spatial distributions of feature expression with highest resolution. Second, after segmentation, expression values or cell-level metadata (e.g. cell-type information) can be visualised on segmented cell areas. This package contains functions for the visualisation of multiplexed read-outs and cell-level information obtained by multiplexed imaging technologies. The main functions of this package allow 1. the visualisation of pixel-level information across multiple channels, 2. the display of cell-level information (expression and/or metadata) on segmentation masks and 3. gating and visualisation of single cells.
Authors:
cytomapper_1.25.0.tar.gz
cytomapper_1.25.0.zip(r-4.7)cytomapper_1.25.0.zip(r-4.6)cytomapper_1.25.0.zip(r-4.5)
cytomapper_1.25.0.tgz(r-4.6-any)cytomapper_1.25.0.tgz(r-4.5-any)
cytomapper_1.25.0.tar.gz(r-4.7-any)cytomapper_1.25.0.tar.gz(r-4.6-any)
cytomapper_1.25.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
cytomapper/json (API)
| # Install 'cytomapper' in R: |
| install.packages('cytomapper', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/bodenmillergroup/cytomapper/issues
Datasets:
- pancreasImages - Example CytoImageList object of image files
- pancreasMasks - Example CytoImageList object of segmentation masks
- pancreasSCE - Example SingleCellExperiment object
On BioConductor:cytomapper-1.25.0(bioc 3.24)cytomapper-1.24.0(bioc 3.23)
immunooncologysoftwaresinglecellonechanneltwochannelmultiplecomparisonnormalizationdataimportbioimagingimaging-mass-cytometrysingle-cellspatial-analysis
Last updated from:7f3973c8cc. Checks:1 WARNING, 7 NOTE, 2 OK. Indexed: yes.
The latest version of this package failed to build. Look at thebuild logs for more information.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| bioc-checks | WARNING | 243 | ||
| linux-devel-x86_64 | NOTE | 918 | ||
| source / vignettes | OK | 374 | ||
| linux-release-x86_64 | NOTE | 828 | ||
| macos-release-arm64 | NOTE | 441 | ||
| macos-oldrel-arm64 | NOTE | 423 | ||
| windows-devel | NOTE | 1088 | ||
| windows-release | NOTE | 1152 | ||
| windows-oldrel | NOTE | 1125 | ||
| wasm-release | OK | 203 |
Exports:channelNameschannelNames<-coercecompImageCytoImageListcytomapperShinygetChannelsgetImagesloadImagesmeasureObjectsmergeChannelsnormalizeplotCellsplotPixelsscaleImagessetChannels<-setImages<-show
Dependencies:abindaskpassbase64encbeeswarmBHBiobaseBiocFileCacheBiocGenericsbiocmakeBiocParallelbitbit64bitopsblobbslibcachemclicodetoolscommonmarkcpp11curlDBIdbplyrDelayedArraydigestdir.expirydplyrEBImageevaluatefarverfastmapfftwtoolsfilelockfontawesomeformatRfsfutile.loggerfutile.optionsgenericsGenomicRangesggbeeswarmggplot2gluegridExtragtableh5mreadHDF5Arrayhighrhtmltoolshtmlwidgetshttpuvhttr2IRangesisobandjpegjquerylibjsonliteknitrlabelinglambda.rlaterlatticelifecyclelocfitmagickmagrittrMatrixMatrixGenericsmatrixStatsmemoisemimennlsopensslotelpillarpkgconfigpngpromisespurrrR6rappdirsrasterRColorBrewerRcppRCurlrhdf5rhdf5filtersRhdf5librjsonrlangrmarkdownRSQLiteS4ArraysS4VectorsS7sassscalesSeqinfoshinyshinydashboardSingleCellExperimentsnowsourcetoolsspSparseArraySpatialExperimentstringistringrSummarizedExperimentsvglitesvgPanZoomsyssystemfontsterratextshapingtibbletidyrtidyselecttifftinytexutf8vctrsviporviridisviridisLitewithrxfunxtableXVectoryaml
Visualization of imaging cytometry data in R
Last update: 2021-09-15
Started: 2020-05-07
On disk storage and handling of images
Introduction | Reading in data to disk | Converting from on disk to memory and back | Effects on package functionality | Session info | References
Last update: 2021-04-23
Started: 2021-03-20
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Performs channel compensation on multi-channel images | compImage |
| S4 class for list of images | coerce,ANY,CytoImageList-method coerce,list,CytoImageList-method CytoImageList CytoImageList-class show,CytoImageList-method |
| Manipulating CytoImageList objects | CytoImageList-manipulation normalize normalize,CytoImageList-method scaleImages scaleImages,CytoImageList-method |
| Getting and setting the channel and image names | channelNames channelNames,CytoImageList-method channelNames<- channelNames<-,CytoImageList-method CytoImageList-naming names,CytoImageList-method names<-,CytoImageList-method |
| General subsetting methods for CytoImageList objects | CytoImageList-subsetting getChannels getChannels,CytoImageList-method getImages getImages,CytoImageList-method mergeChannels setChannels<- setChannels<-,CytoImageList-method setImages<- setImages<-,CytoImageList-method [<-,CytoImageList,ANY,ANY,CytoImageList-method [[<-,CytoImageList,ANY,ANY-method |
| Shiny application to visualise gated cells on images | cytomapperShiny |
| Read images into CytoImageList object | loadImages |
| Compute morphological and intensity features from objects on images. | measureObjects |
| Example CytoImageList object of image files | pancreasImages |
| Example CytoImageList object of segmentation masks | pancreasMasks |
| Example SingleCellExperiment object | pancreasSCE |
| Function to visualize cell-level information on segmentation masks | plotCells |
| Function to visualize pixel-level information of multi-channel images | plotPixels |
| Further plotting parameters for the cytomapper package | plotting-param |