slalom
Bioc currentFactorial Latent Variable Modeling of Single-Cell RNA-Seq Data
Release Lineage
Entered 3.6 · Oct 31, 2017
Current · Requires R 4.6
Description
slalom is a scalable modelling framework for single-cell RNA-seq data that uses gene set annotations to dissect single-cell transcriptome heterogeneity, thereby allowing to identify biological drivers of cell-to-cell variability and model confounding factors. The method uses Bayesian factor analysis with a latent variable model to identify active pathways (selected by the user, e.g. KEGG pathways) that explain variation in a single-cell RNA-seq dataset. This an R/C++ implementation of the f-scLVM Python package. See the publication describing the method at https://doi.org/10.1186/s13059-017-1334-8.
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People
- Davis McCarthy author maintainer
- Florian Buettner author
- John Marioni author
- Naruemon Pratanwanich author
- Oliver Stegle author