Reference-free Cell-Type Deconvolution of Multi-Cellular Spatially Resolved Transcriptomics Data

Documentation for package ‘STdeconvolve’ version 1.8.0

annotateCellTypesGSEA	Match deconvolved cell-types to ground truth cell-types based on transcriptional profiles
cleanCounts	Filter a counts matrix
correlationPlot	Generate heatmap of correlations
fitLDA	Find the optimal number of cell-types K for the LDA model
getBetaTheta	Pull out cell-type proportions across pixels (theta) and cell-type gene probabilities (beta) matrices from fitted LDA models from fitLDA
getCorrMtx	Find Pearson's correlations between topics (cell-types) with respect to their proportions across documents (pixels), i.e. thetas, or gene probabilities, i.e. betas.
getOverdispersedGenes	Normalize gene expression variance relative to transcriptome-wide expectations (Modified from SCDE/PAGODA2 code)
lsatPairs	Function to get Hungarian sort pairs via clue::lsat
mOB	Spatial transcriptomics of the mouse olfactory bulb
optimalModel	Get the optimal LDA model
perplexityPlot	Plot the perplexity and rare cell-types versus fitted Ks
preprocess	Pre-process ST pixel gene count matrices to construct corpus for input into LDA
restrictCorpus	Restrict to informative words (genes) for topic modeling
topGenes	Returns top n genes of each deconvolved cell-type for a given beta matrix
vizAllTopics	Visualize all topic proportions across pixels with 'scatterpie'
vizGeneCounts	Visualize gene counts for a given gene in the pixels. Can also see group assignment of spots.
vizTopic	Visualize pixel proportions of a single cell-type.