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junjunlab
ClusterGVis:One-Step to Cluster and Visualize Gene Expression Data
Streamlining the clustering and visualization of time-series gene expression data from RNA-Seq experiments, this tool supports fuzzy c-means and k-means clustering algorithms. It is compatible with outputs from widely-used packages such as 'Seurat', 'Monocle', and 'WGCNA', enabling seamless downstream visualization and analysis. See Lokesh Kumar and Matthias E Futschik (2007) <doi:10.6026/97320630002005> for more details.
Maintained by Jun Zhang. Last updated 23 days ago.
sequencingclusterprofilersummarizedexperimentmfuzzcomplexheatmapgene-clusteringgene-expressionvisualization
281 stars 6.80 score 30 scripts
bioc
CellMixS:Evaluate Cellspecific Mixing
CellMixS provides metrics and functions to evaluate batch effects, data integration and batch effect correction in single cell trancriptome data with single cell resolution. Results can be visualized and summarised on different levels, e.g. on cell, celltype or dataset level.
Maintained by Almut Lütge. Last updated 5 months ago.
singlecelltranscriptomicsgeneexpressionbatcheffect
7 stars 6.35 score 64 scripts