Abstract
AbstractSpatially 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-sampleSpatialTranscriptomics dataANalysis with cross-sample transcriptional similarityGuidance), 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 ofMUSTANGin revealing biological insights inherent in cellular characterization of tissue samples under the study. MUSTANG is publicly available at athttps://github.com/namini94/MUSTANG
Publisher
Cold Spring Harbor Laboratory
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