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import scimap as sm

Preprocessing: pp

Scimap provides a suite of tools to preprocess the data for subsequent analysis.

Function Short Description
sm.pp.mcmicro_to_scimap mcmicro output to scimap compatible object
sm.pp.rescale Manual/Auto gate based scaling of data

Tools: tl

sm.tl.umap Dimensionality Reduction using UMAP
sm.tl.cluster Cluster or sub-cluster single-cells using a variety of algorithms
sm.tl.foldchange Compute foldchange in phenotypes between samples/ROIs
sm.tl.phenotype_cells Probability distribution based cell phenotyping
sm.tl.spatial_aggregate Aggregates of cell-types with local neighborhood
sm.tl.spatial_count Distribution of cell-types with local neighborhood
sm.tl.spatial_distance Computes nearest distance between all phenotypes for every cell
sm.tl.spatial_expression Distribution of spatial expression with local neighborhood
sm.tl.spatial_interaction cell–cell interactions analysis
sm.tl.spatial_lda Latent Dirichlet Allocation (LDA) modelling for spatial motifs
sm.tl.spatial_pscore Scoring proximity between user defined cell types
sm.tl.spatial_similarity_search Search for similar looking regions within and across images

Plotting: pl

sm.pl.umap Overlays markers on UMAP
sm.pl.gate_finder Overlays gating positivity on the image for manual gating
sm.pl.image_viewer Opens the image with overlays on a napari browser
sm.pl.stacked_barplot Generate a stacked barplot from any two columns of categorical data
sm.pl.pie Generate a pieplot of cell-type proportion or any categorical data
sm.pl.foldchange vizualize foldchange in phenotypes between samples/ROIs
sm.pl.voronoi Generate a voronoi diagram and color it with categorical data
sm.pl.spatial_interaction Heatmap of cell–cell interaction analysis
sm.pl.spatial_distance Visualize distance between phenotypes
sm.pl.spatial_pscore Bar plot of the derived Spatial Proximity Scores
sm.pl.addROI_image Add ROI's with napari browser

Helper Functions: hl

sm.hl.classify Quickly classify cells based on pos/negativity of list of markers
sm.hl.rename Quickly rename values within columns based on dict mapping
sm.hl.animate Create a animated scatter plot of embedding -> physical location
sm.hl.scimap_to_csv Export scimap object to CSV
sm.hl.addROI_omero Add ROI's extracted from Omero to Scimap object
sm.hl.dropFeatures Handy Function to subset the adata object