spacemake 0.7.2

A bioinformatic pipeline for the analysis of spatial transcriptomic data

Spacemake: processing and analysis of large-scale spatial transcriptomics data

Spacemake is a modular, robust, and scalable spatial transcriptomics pipeline built in Snakemake and Python. Spacemake is designed to handle all major spatial transcriptomics datasets and can be readily configured for other technologies. It can process and analyze several samples in parallel, even if they stem from different experimental methods. Spacemake's unified framework enables reproducible data processing from raw sequencing data to automatically generated downstream analysis reports. Spacemake is built with a modular design and offers additional functionality such as sample merging, saturation analysis, and analysis of long reads as separate modules.

If you find Spacemake useful in your work, consider citing it:

Spacemake: processing and analysis of large-scale spatial transcriptomics data
Tamas Ryszard Sztanka-Toth, Marvin Jens, Nikos Karaiskos, Nikolaus Rajewsky
GigaScience, Volume 11, 2022, giac064

Documentation can be found here.