JSON
Larsson L, Franzén L, Ståhl PL, Lundeberg J
Bioinformatics 39 (10) - [2023-10-03; online 2023-10-17]
Spatially resolved transcriptomics technologies generate gene expression data with retained positional information from a tissue section, often accompanied by a corresponding histological image. Computational tools should make it effortless to incorporate spatial information into data analyses and present analysis results in their histological context. Here, we present semla, an R package for processing, analysis, and visualization of spatially resolved transcriptomics data generated by the Visium platform, that includes interactive web applications for data exploration and tissue annotation. The R package semla is available on GitHub (https://github.com/ludvigla/semla), under the MIT License, and deposited on Zenodo (https://doi.org/10.5281/zenodo.8321645). Documentation and tutorials with detailed descriptions of usage can be found at https://ludvigla.github.io/semla/.
PubMed 37846051
DOI 10.1093/bioinformatics/btad626
Crossref 10.1093/bioinformatics/btad626
pmc: PMC10597621
pii: 7319366