MUSTANG: Multi-sample spatial transcriptomics data analysis with cross-sample transcriptional similarity guidance.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 38800365.
- Also identified by DOI 10.1016/j.patter.2024.100986 and PMC identifier 11117058.
- Licence recorded as CC BY-NC-ND.
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Abstract
Spatially resolved transcriptomics has revolutionized genome-scale transcriptomic profiling by providing high-resolution characterization of transcriptional patterns. Here, we present our spatial transcriptomics analysis framework, MUSTANG (MUlti-sample Spatial Transcriptomics data ANalysis with cross-sample transcriptional similarity Guidance), which is capable of performing multi-sample spatial transcriptomics spot cellular deconvolution by allowing both cross-sample expression-based similarity information sharing as well as spatial correlation in gene expression patterns within samples. Experiments on a semi-synthetic spatial transcriptomics dataset and three real-world spatial transcriptomics datasets demonstrate the effectiveness of MUSTANG in revealing biological insights inherent in the cellular characterization of tissue samples under study.