ArticlePatterns (New York, N.Y.)2024
MUSTANG: Multi-sample spatial transcriptomics data analysis with cross-sample transcriptional similarity guidance.
Article in Patterns (New York, N.Y.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- iS2C2: a cointelligent platform for mechanistic discovery of disease cellular crosstalk.Signal transduction and targeted therapy · 2026Article
- A narrative review of spatial multi-omics and organ-on-a-chip technologies for cardio-cerebral-renal crosstalk.Frontiers in bioengineering and biotechnology · 2026Review
- Detection of mRNA Transcript Variants.Genes · 2025Review
- Deep topic modeling of spatial transcriptomics in the rheumatoid arthritis synovium identifies distinct classes of ectopic lymphoid structures.bioRxiv : the preprint server for biology · 2025Article
- Systems immunology insights into brain metastasis.Trends in immunology · 2024Review
- MUSTANG: Multi-sample spatial transcriptomics data analysis with cross-sample transcriptional similarity guidance.Patterns (New York, N.Y.) · 2024Article
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Authors and funding
8 authors.
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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.
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