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Intracellular Spatial Transcriptomic Analysis Toolkit (InSTAnT)

Imaging-based spatial transcriptomics technologies such as MERFISH offer snapshots of cellular processes in unprecedented detail, but new analytic tools are needed to realize their full potential. We present InSTAnT, a computational toolkit for extracting molecular relationships from spatial transcr...

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Detalles Bibliográficos
Autores principales: Kumar, Anurendra, Schrader, Alex W., Boroojeny, Ali Ebrahimpour, Asadian, Marisa, Lee, Juyeon, Song, You Jin, Zhao, Sihai Dave, Han, Hee-Sun, Sinha, Saurabh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Journal Experts 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9901031/
https://www.ncbi.nlm.nih.gov/pubmed/36747718
http://dx.doi.org/10.21203/rs.3.rs-2481749/v1
Descripción
Sumario:Imaging-based spatial transcriptomics technologies such as MERFISH offer snapshots of cellular processes in unprecedented detail, but new analytic tools are needed to realize their full potential. We present InSTAnT, a computational toolkit for extracting molecular relationships from spatial transcriptomics data at the intra-cellular resolution. InSTAnT detects gene pairs and modules with interesting patterns of mutual co-localization within and across cells, using specialized statistical tests and graph mining. We showcase the toolkit on datasets profiling a human cancer cell line and hypothalamic preoptic region of mouse brain. We performed rigorous statistical assessment of discovered co-localization patterns, found supporting evidence from databases and RNA interactions, and identified subcellular domains associated with RNA-colocalization. We identified several novel cell type-specific gene co-localizations in the brain. Intra-cellular spatial patterns discovered by InSTAnT mirror diverse molecular relationships, including RNA interactions and shared sub-cellular localization or function, providing a rich compendium of testable hypotheses regarding molecular functions.