STdeconvolve

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


Bioconductor version: Release (3.20)

STdeconvolve as an unsupervised, reference-free approach to infer latent cell-type proportions and transcriptional profiles within multi-cellular spatially-resolved pixels from spatial transcriptomics (ST) datasets. STdeconvolve builds on latent Dirichlet allocation (LDA), a generative statistical model commonly used in natural language processing for discovering latent topics in collections of documents. In the context of natural language processing, given a count matrix of words in documents, LDA infers the distribution of words for each topic and the distribution of topics in each document. In the context of ST data, given a count matrix of gene expression in multi-cellular ST pixels, STdeconvolve applies LDA to infer the putative transcriptional profile for each cell-type and the proportional representation of each cell-type in each multi-cellular ST pixel.

Author: Brendan Miller [aut, cre] , Jean Fan [aut]

Maintainer: Brendan Miller <bmill3r at gmail.com>

Citation (from within R, enter citation("STdeconvolve")):

Installation

To install this package, start R (version "4.4") and enter:


if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("STdeconvolve")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

Reference Manual PDF
NEWS Text

Details

biocViews Bayesian, GeneExpression, RNASeq, Software, Spatial, Transcriptomics, Visualization
Version 1.9.0
In Bioconductor since BioC 3.15 (R-4.2) (2.5 years)
License GPL-3
Depends R (>= 4.1)
Imports topicmodels, BiocParallel, Matrix, methods, mgcv, ggplot2, scatterpie, viridis, slam, stats, clue, liger, reshape2, graphics, grDevices, utils
System Requirements
URL https://jef.works/STdeconvolve/
Bug Reports https://github.com/JEFworks-Lab/STdeconvolve/issues
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Suggests knitr, BiocStyle, rmarkdown, testthat, rcmdcheck, gplots, gridExtra, hash, dplyr, parallel
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Package Archives

Follow Installation instructions to use this package in your R session.

Source Package
Windows Binary (x86_64)
macOS Binary (x86_64)
macOS Binary (arm64) STdeconvolve_1.9.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/STdeconvolve
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/STdeconvolve
Bioc Package Browser https://code.bioconductor.org/browse/STdeconvolve/
Package Short Url https://bioconductor.org/packages/STdeconvolve/
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