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bioRxiv · 10.1101/2023.09.08.556895

MUSTANG: MUlti-sample Spatial Transcriptomics data ANalysis with cross-sample transcriptional similarity Guidance

Niyakan, S.·Sheng, J.·Cao, Y.·Zhang, X.·Xu, Z.·Wu, L.·Wong, S. T.·Qian, X.
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Abstract

AO_SCPLOWBSTRACTC_SCPLOWSpatially resolved transcriptomics has revolutionized genome-scale transcriptomic profiling by providing high-resolution characterization of transcriptional patterns. We here 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 two real-world spatial transcriptomics datasets demonstrate the effectiveness of MUSTANG in revealing biological insights inherent in cellular characterization of tissue samples under the study. MUSTANG is publicly available at at https://github.com/namini94/MUSTANG

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Niyakan, S., Sheng, J., Cao, Y., Zhang, X., Xu, Z., Wu, L., Wong, S. T., Qian, X.. 2023-09-12. MUSTANG: MUlti-sample Spatial Transcriptomics data ANalysis with cross-sample transcriptional similarity Guidance. https://doi.org/10.1101/2023.09.08.556895

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