SpaMTP is an R package designed for the integrative analysis of spatial metabolomics and spatial transcriptomics data. SpaMTP inherits functionalities from two well established R packages (Cardinal and Seurat) to present a user-friendly platform for integrative spatial-omics analysis. Build on the foundation of a Seurat Class Object, this package has three major functionalities which include; (1) mass-to-charge ratio (m/z) metabolite annotation, (2) various downstream statistical analysis including differential metabolite expression and pathway analysis, and (3) integrative spatial-omics analysis. In addition, this package includes various functions for data visualisation and data import/export, permitting flexible usage with other established R and Python packages.
Please head to the SpaMTP website for stable documentation, including the RaMP 3.0 indexed metabolite annotation pipeline. The latest experimental functionality is available from the developmental branch and its developmental documentation site.
SpaMTP is now published in Nature Methods: SpaMTP: integrative statistical analysis and visualization of spatial metabolomics and transcriptomics data.
You can install the current version of SpaMTP from GitHub with:
if (!require("devtools", quietly = TRUE))
install.packages("devtools")
devtools::install_github("GenomicsMachineLearning/SpaMTP")To test the latest developmental annotation and integration pipelines:
devtools::install_github(
"GenomicsMachineLearning/SpaMTP",
ref = "developmental"
)For tutorials and more information please visit the SpaMTP website
If SpaMTP contributes to your work, please cite:
Causer, A., Lu, T., Kriel, J. et al. SpaMTP: integrative statistical analysis and visualization of spatial metabolomics and transcriptomics data. Nature Methods 23, 1501–1506 (2026). https://doi.org/10.1038/s41592-026-03140-8
The citation can also be retrieved directly in R:
citation("SpaMTP")SpaMTP is currently maintained by Tianyao Lu (GitHub, email). Andrew Causer remains credited as an original author and former maintainer.
To download the image:
wget -c https://downloads.gmllab.com/SpaMTP/spamtp-1.1.sif
Verify it download correctly:
wget -q -O - https://downloads.gmllab.com/SpaMTP/spamtp-1.1.sif.md5 | md5sum -c -
Or to create an Apptainer image from scratch (you need the environment-linux.yml, dependencies.R and spamtp.def files):
apptainer build spamtp.sif spamtp.def
To reproduce the dependencies and install SpaMTP into a conda environment:
conda create --prefix [some-directory]/conda/spamtp python=3.10 r-base=4.4 imagemagick --y
conda activate [some-directory]/conda/spamtp
conda install -c conda-forge jupyter libconfig fontconfig freetype libtiff r-irkernel --y
conda install --no-update-deps -c conda-forge r-here r-matrix r-Seurat r-SeuratObject r-hdf5r r-ggplot2 r-reshape2 r-patchwork fftw r-RCurl r-jpeg r-locfit r-ontologyindex --y
conda install --no-update-deps -c conda-forge r-fields r-ggdendro r-ggnewscale r-magick r-naturalsort r-pheatmap r-sf r-shinyjs r-zeallot r-r.utils --y
conda install --no-update-deps -c bioconda bioconductor-BiocGenerics bioconductor-enhancedvolcano bioconductor-biocparallel --y
conda install --no-update-deps -c bioconda bioconductor-protgenerics bioconductor-s4vectors bioconductor-biobase --y
conda install --no-update-deps -c bioconda bioconductor-edger bioconductor-fgsea bioconductor-limma bioconductor-scater bioconductor-singlecellexperiment --y
conda install --no-update-deps -c bioconda bioconductor-delayedmatrixstats bioconductor-hdf5array bioconductor-rhdf5 bioconductor-rhdf5lib --y
conda install --no-update-deps -c bioconda bioconductor-msnbase bioconductor-ebimage==4.48.0-0 --y
Rscript dependencies.R