
Changelog
semla 1.4.0
2025-09-08
Changes
- Increased versions of semla’s dependencies:
- Seurat v5 or above
- ggplot2 v3.5.2 or above
-
GetSpatialNetwork()can compute the network on either array or pixel spot coordinates. - Cleaned up warnings that come inside testing
semla 1.3.2
2025-07-4
Changes
- Bug fix for
UpdateSeuratForSemla()when dealing with VisiumV2 data. VisiumV2 assays can contain both VisiumHD and Visium data. With Visium data, regular array coordinates cannot be returned, which could cause issues when running specific plotting methods downstream. Thus, we recommend usingsemla’sReadVisiumData()in order to read the data into memory.
semla 1.3.1
2025-03-19
Changes
If the spot barcode IDs are missing a “-N” (e.g. “-1”) suffix (like is standard in Visium data), it will be added to the IDs when running
ReadVisiumData(). This ensures that multiple samples can be added and merged properly without conflicts with unique barcode identities.Minor edits to the backend code for plotting functions
semla 1.3.0
2025-02-26
Added
- Functionalities added for creating a spatial multimodal object using the new function
CreateMultiModalObject(). This new function takes two objects, which have had their pixel coordinates aligned to each other beforehand, and joins them into a new object where the spatial points from the second “mapping” modality are mapped and aggregated onto the first “reference” modality. The data in the two modalities are stored as separate assays in the new object.
Changes
- Changed the appearance of the color scalebar in
MapFeatures()andMapMultipleFeatures()so that the ticks and outline colors are black and have the same linewidth. -
MapFeaturesSummary()now has a default option set for thesubplot_typeargument (default = “violin”).
semla 1.2.1
2025-01-24
Bug fixes
- Fixed an issue with the
RadialDistance()function to make it possible to pass additional arguments, such asmaxDistandnNeighbors. Related to Issue #36
semla 1.2.0
2024-09-27
Bug fixes
Dealt with an issue in
MapFeaturesandMapLabelsif the specified column contains NA values and when using SeuratObject v.5.When running
RegionNeighborsand specifying a column in which labels contain any blank spaces, the function will abort and a message will be provided. (#20)
Added
- Compatibility with parquet file format, used in Visium HD, when loading coordinate files using the
LoadSpatialCoordinatesfunction (used inReadVisiumData). - New arguments,
shapeandspot_side, within theMapFeatures,MapLabels,MapFeaturesSummary,MapLabelsSummary, andMapMultipleFeaturesfunctions to allow for square pixel plotting, particularly useful when working with Visium HD data. - A new vignette to demonstrate how to work with Visium HD data has also been added to the website.
- Added a new argument,
image_use, to theUpdateSeuratFromSemlafunction, allowing the user to decide if they want to put the raw or the transformed image in the new object (#33). - Optional alternative to compute p-values when calculating spatial autocorrelation scores using
CorSpatialFeatures. The p-values are computed using the Student t Distribution, and adjusted p-values are calculated using the Benjamini & Hochberg (BH, or FDR) method. (#22)
semla 1.1.6
2023-09-19
Bug fixes
- Fixed bug in
RunLocalGwhenstore_in_metadata = FALSEand no alternative hypothesis is provided. - Fixed bug in
TileImagewhen using multiple threads on linux.
Changes
- Modified behaviour of
mode = "heatmap"inPlotFeatureLoadingsto make sure that features are ordered by their highest dimensionality reduction value. - Updated NNMF vignette with a new data set.
- Changed deprecated
ggplot2function arguments inAnglePlotandMapFeaturesSummary. - Changed example
Seuratobject to contain basic array coordinates.
Added
- Option to set
launch.browserinFeatureViewer. For instance, users can selaunch.browser = getOption("viewer")inFeatureViewerto launch the app in the RStudio viewer window. -
CreateStaffliObjectnow accepts basic array coordinates to be stored inmeta_dataslot. These coordinates are defined on the capture array grid of a 10x Genomics Visium slide and do not match the H&E images.
semla 1.1.4
2023-09-04
Bug fixes
- Fixed bug in
LoadScaleFactors - Fixed bug in
FeatureViewerwhen handling data sets with spots located outside the H&E image
Added
- Added support for conversion of
Seuratobjects with Slide-seq data inUpdateSeuratForSemla - Added option to color background and titles in
ImagePlot - Added support for Visium + IF data in
LoadAndMergeMatricesandReadVisiumData - Added
renv.lockfile for installing semla and its dependencies withrenv
semla 1.1.0
2023-08-14
Added
- Added helper function for
Staffliobjects:-
GetScaleFactorsto fetchtibblewith scale factor related information
-
-
GetImagesto fetch images -
GetImageInfoto fetchtibblewith image related information -
ReplaceImagePathsto validate and update image paths - Added
UpdateSeuratForSemlato makeSeuratobjects with VisiumV1 data compatible withsemla - Added
LoadAnnotationCSVto load annotations exported from Loupe Browser
Changes
- Improved verbosity
- Reduced size of example data
- Updated function documentation
- Updated function examples
- Added option to load images from URL instead of local path (
LoadImagesandReplaceImagePaths) - Added option to use multiple cores for
ExportDataForViewer - Fixed bug in
RadialDistancewhen no spots are available after removing singletons - Fixed bug in
MergeSTDatawhen merging two or more objects containing multiple tissue sections - Fixed bug in
MapMultipleFeatureswhen NA values are present - Updated data loaders for increased compatibility with CytAssist data. Minor bug fixes for edge cases when spots are located outside of the H&E image
- Fixed bug in
LoadAndMergeMatriceswhen loading data from a data folder output by Space Ranger - Changed output of
AdjustTissueCoordinateswhich now returns unadjusted y-axis values
semla 1.0.0
2023-03-24
We are excited to announce the first release of our R package, semla.
The package is designed to process, analyze and visualize Spatially Resolved Transcriptomics (SRT) data.
Key features of this release include:
- Interactive data visualization and annotation with the
FeatureViewerweb app - Spatially aware analysis methods:
RegionNeighbors,RadialDistance,CorSpatialFeatures,RunLocalG,RunLabelAssortativityTest,RunNeighborhoodEnrichmentTest,CutSpatialNetwork - Visualization methods:
MapFeatures,MapLabels - Image processing:
MaskImages,RigidTransformImages,RunAlignment - Cell type mapping:
RunNNLS
We would like to express our gratitude to Javier Morlanes and Marcos Machado who contributed to this release. We appreciate your feedback, suggestions, and bug reports.
We invite users to download and install the development version of the package from our GitHub repo and explore the features and functionality. Please feel free to provide feedback and suggestions for future improvements.
Thank you for your support and we look forward to continuing to enhance and improve this package.
Sincerely,
Ludvig Larsson and Lovisa Franzén