Changes in version 2.1.2 - Update filterCommunication to allow identifying consistent cell-cell communication across samples when mutiple samples/replicates/batches are merged as an input for CellChat analysis. - Update computeCommunProb where the ECM-receptor signaling is now assumed as diffusible signaling when analyzing spatial transcrptomics. - Update 'updateCellChat' to change object@meta$slices to object@meta$samples in order to identify consistent cell-cell communication across samples. - Typos in CellChatDB were fixed. Updated functions with minor changes Functions that have been updated for analyzing spatial transcriptomics and perform comparison analysis, including createCellChat, 'updateCellChat', computeCommunProb,filterCommunication, spatialFeaturePlot, spatialDimPlot, netVisual_spatial, netVisual_aggregate, netVisual, computeRegionDistance, StackedVlnPlot. Changes in version 2.1.1 (2023-12-12) - Enable to flexibly infer contact-dependent or juxtacrine signaling from any type of spatial transcriptomics data by defining the contact.range in computeCommunProb. - Change scale.factors to spatial factors. Updated functions with minor changes Functions that have been updated for analyzing spatial transcriptomics and perform comparison analysis, including createCellChat, 'updateCellChat', computeCommunProb,computeRegionDistance, netMappingDEG, computeEnrichmentScore, netVisual_bubble, identifyOverExpressedInteractions, identifyOverExpressedGenes. Changes in version 2.1.0 (2023-11-26) - CellChat v2 now enables the inferrence of cell-cell communication from multiple spatially resolved transcriptomics datasets. Users should update the previously calculated individual CellChat object for spatial transcriptomics data analysis via updateCellChat function. - We add Frequently Asked Questions (FAQ) when analyzing spatially resolved transcriptomics datasets, particularly on how to apply CellChat to different technologies of spatial transcriptomics data, including sequencing-based and in-situ imaging-based readouts. In addition, we redefine the scale.factors for easier interpretation when applying other spatial technologies. Updated functions with changes Functions that have been updated for analyzing spatial transcriptomics, including CellChat-class, createCellChat, 'updateCellChat', computeCommunProb,computeRegionDistance, computeCellDistance, subsetDB, spatialFeaturePlot, spatialDimPlot, netVisual_spatial, netVisual_aggregate, netVisual. Changes in version 2.0.0 (2023-11-01) CellChat v2 is an updated version that includes - inference of spatially proximal cell-cell communication between interacting cell groups from spatially resolved transcriptomics - expanded database CellChatDB v2 by including more than 1000 protein and non-protein interactions such as metabolic and synaptic signaling, and by adding rich annotations to each ligand-receptor pair. A function named updateCellChatDB is also provided for easily updating CellChatDB. - new functionalities enabling easily interface with other computational tools for single-cell data analysis and cell-cell communication analysis - interactive web browser function to allow exploration CellChat outputs of spatially proximal cell-cell communication Updated functions with minor changes Functions that have been updated for analyzing spatial imaging data, such as netVisual_circle, netVisual, netVisual_aggregate, netVisual_individual, pieChart, showDatabaseCategory, subsetDB, identifyOverExpressedGenes, computeRegionDistance, computeCommunProb, '' New added functions runCellChatApp, updateCellChatDB, updateCCC_score, findEnrichedSignaling, spatialFeaturePlot, spatialDimPlot Changes in version 1.6.0 (2022-11-12) CellChat is now applicable to spatial imaging data. We showcase its application to 10X Visium data. When spatial locations of spots/cells are available, CellChat infers spatial-informed cell-cell communication between interacting cell groups. CellChat restricts cell-cell communication within the maximum interaction/diffusion length of molecules. A brief tutorial for spatial imaging data analysis is available in the tutorial directory. CellChat's various functionality can be used for further data exploration, analysis, and visualization. We have redesigned the structure of CellChat object. When loading previous CellChat object (version < 1.6.0), please update the object via updateCellChat. Updated functions with minor changes Functions that have been updated for analyzing spatial imaging data, such as CellChat-class, createCellChat, updateCellChat, computeCommunProb, netVisual, netVisual_aggregate, netVisual_individual New added functions netVisual_spatial, computeRegionDistance Changes in version 1.5.0 (2022-08-06) We have now presented our comparison framework for systematically detecting dysregulated cell-cell communication across biological conditions, and then utilized it to study the aging-induced signaling changes during skin wound healing. Our results not only present general communication rules and signaling mechanisms in wound healing associated with aging, but also provide a paradigm for other researchers to study cell-cell communication in other contexts. Please check out our paper (Vu#, Jin#, Sun# et al., Cell Reports, 2022) for the detailed methods and applications. Changes in version 1.4.0 (2022-05-07) Updated functions with minor changes A number of functions have been updated with enhanced functionalities, such as rankNet, netVisual_aggregate, netVisual_circle, 'plotGeneExpression', netVisual_embedding. New added functions computeEnrichmentScore, 'netVisual_barplot', 'barPlot' Changes in version 1.1.3 (2021-08-14) Updated functions with minor changes netAnalysis_computeCentrality, netVisual_embeddingPairwise, netAnalysis_signalingChanges_scatter NB: The method for computing the 'influencer' metric in the function netAnalysis_computeCentrality has been changed due to the issue that "lower" mode gives different results when re-ordering the matrix. The results changed, but it looks like the dominant patterns do not change, i.e., the top cell groups ranked based on this metrix retain the same. Changes in version 1.1.2 (2021-07-10) New added functions - Add netAnalysis_diff_signalingRole_scatter for 2D visualization of differential signaling roles of each cell group when comparing mutiple datasets. Updated functions with minor changes netVisual, netVisual_aggregate, netVisual_individual, netVisual_hierarchy1, netVisual_hierarchy2,netVisual_circle,createCellChat,netAnalysis_computeCentrality ,netAnalysis_signalingRole_scatter, netAnalysis_signalingChanges_scatter Important changes - Add thresh = 0.05 in netAnalysis_computeCentrality to only consider the significant interactions. This will slightly change (very likely quantitative instead of qualitative change) the results computed by previous version of CellChat. - In the updated netAnalysis_computeCentrality, we now also compute unweighted outdegree (i.e., the total number of outgoing links) and indegree (i.e., the total number of incoming links). - netAnalysis_signalingRole_scatter and netAnalysis_signalingChanges_scatter now support the comparison of the total number of outgoing and incoming links. - Change the default setting for visualizing cell-cell communication network: 1) using circle plot instead of hierarchy; 2) using the same node size instead of different size (setting vertex.weight = NULL will give different size as in previous version of CellChat). Changes in version 1.1.1 (2021-06-19) New added functions - Add updateClusterLabels to update cell cluster labels without re-running the time-consuming function computeCommunProb. Updated functions with minor changes netAnalysis_signalingRole_scatter, setIdent, netVisual_diffInteraction, sketchData, identifyOverExpressedGenes,netEmbedding,runUMAP Changes in version 1.1.0 (2021-04-26) New added functions - Add subsetCellChat to create a object using a portion of cells - Add computeAveExpr to compute the average expression per cell group - Add sketchData to downsample the single cell data for faster calculation - Add netAnalysis_signalingChanges_scatter to identify the signaling changes associated with one cell group Important changes - computeCommunProb now supports a faster calculation and displays a ProgressBar - computeCommunProbPathway now returns the significant pathways that are ordered based on the total communication probabilities Publish a new release - The first release was published as version 1.0.0 before updating to version 1.1.0 Changes in version 1.0.0 (2021-02-17) - CellChat paper is now officially published (Jin et al., Nature Communications, 2021). Compared to the preprint, we have now experimentally validated CellChat's predictions on embryonic skin using RNAscope technique, applied CellChat to a human diseased skin dataset and updated many others. - We have now developed a standalone CellChat Shiny App for interactive exploration of the cell-cell communication analyzed by CellChat. Want to share your results with your collaborators like biologists for further exploration? Try it out! Changes in version 0.5.0 (2021-01-05) - Slight changes of CellChat object (Please update your previously calculated CellChat object via updateCellChat()) - Enhanced documentation of functions and tutorials (use help() to check the documentation, e.g., help(CellChat)) - New features for comparison analysis of multiple datasets - Support for creating a new CellChat object from Seurat V3 or SingleCellExperiment object