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

ABSTRACT:

Background

Spatial sequencing methods increasingly gain popularity within RNA biology studies. State-of-the-art techniques quantify messenger RNA expression levels from tissue sections and at the same time register information about the original locations of the molecules in the tissue. The resulting data sets are processed and analyzed by accompanying software that, however, is incompatible across inputs from different technologies.

Findings

Here, we present spacemake, a modular, robust, and scalable spatial transcriptomics pipeline built in Snakemake and Python. Spacemake is designed to handle all major spatial transcriptomics data sets and can be readily configured for other technologies. It can process and analyze several samples in parallel, even if they stem from diffe

SUBMITTER: Sztanka-Toth TR 

PROVIDER: S-EPMC9295369 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature