SNMF (Spatial Non-Negative Matrix Factorization)

SNMF (Spatial Non-negative Matrix Factorization) is a rapid, accurate, and reference-free deconvolution method for sequencing-based spatial transcriptomics data. It extends classical NMF with explicit spatial modeling and is the first spatial transcriptomics deconvolution tool to natively support GPU acceleration, while providing a seamless CPU fallback.

This repository contains the official implementation accompanying the paper:

SNMF: Ultrafast, Spatially-Aware Deconvolution for Spatial Transcriptomics

Installation

This repository contains the package of SNMF, wich can be installed by running:

devtools::install_github("LuisAlonsoEsteban/SNMF")

Before installing SNMF, make sure that the GPUmatrix package is installed and working on your system. See the installation instructions

Usage

Load the SNMF package:

library(SNMF)

This package provides with a toy example of the Triple Negative Breast Cancer (TNBC) dataset, with the 100th most variable genes. You can load it with:

data(tnbc)

which saves this data.frame in a variable called tnbc.

Next, you can preprocess this matrix and generate the $S$ matrix with the following function:

data <- load_data(tnbc)
counts <- data$counts
S <- data$S

Finally, you can run SNMF:

results <- snmf(counts, S, 5, niter=2000, tol=1e-4, num_initializations=10, probs=0.75, seed=42)
H <- results$H
W <- results$W