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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...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Journal Experts
2023
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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 |
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author | Kumar, Anurendra Schrader, Alex W. Boroojeny, Ali Ebrahimpour Asadian, Marisa Lee, Juyeon Song, You Jin Zhao, Sihai Dave Han, Hee-Sun Sinha, Saurabh |
author_facet | Kumar, Anurendra Schrader, Alex W. Boroojeny, Ali Ebrahimpour Asadian, Marisa Lee, Juyeon Song, You Jin Zhao, Sihai Dave Han, Hee-Sun Sinha, Saurabh |
author_sort | Kumar, Anurendra |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9901031 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | American Journal Experts |
record_format | MEDLINE/PubMed |
spelling | pubmed-99010312023-02-07 Intracellular Spatial Transcriptomic Analysis Toolkit (InSTAnT) Kumar, Anurendra Schrader, Alex W. Boroojeny, Ali Ebrahimpour Asadian, Marisa Lee, Juyeon Song, You Jin Zhao, Sihai Dave Han, Hee-Sun Sinha, Saurabh Res Sq Article 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. American Journal Experts 2023-01-27 /pmc/articles/PMC9901031/ /pubmed/36747718 http://dx.doi.org/10.21203/rs.3.rs-2481749/v1 Text en https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use. https://creativecommons.org/licenses/by/4.0/License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License (https://creativecommons.org/licenses/by/4.0/) |
spellingShingle | Article Kumar, Anurendra Schrader, Alex W. Boroojeny, Ali Ebrahimpour Asadian, Marisa Lee, Juyeon Song, You Jin Zhao, Sihai Dave Han, Hee-Sun Sinha, Saurabh Intracellular Spatial Transcriptomic Analysis Toolkit (InSTAnT) |
title | Intracellular Spatial Transcriptomic Analysis Toolkit (InSTAnT) |
title_full | Intracellular Spatial Transcriptomic Analysis Toolkit (InSTAnT) |
title_fullStr | Intracellular Spatial Transcriptomic Analysis Toolkit (InSTAnT) |
title_full_unstemmed | Intracellular Spatial Transcriptomic Analysis Toolkit (InSTAnT) |
title_short | Intracellular Spatial Transcriptomic Analysis Toolkit (InSTAnT) |
title_sort | intracellular spatial transcriptomic analysis toolkit (instant) |
topic | Article |
url | 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 |
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