STmut: a framework for visualizing somatic alterations in spatial transcriptomics data of cancer

Spatial transcriptomic technologies, such as the Visium platform, measure gene expression in different regions of tissues. Here, we describe new software, STmut, to visualize somatic point mutations, allelic imbalance, and copy number alterations in Visium data. STmut is tested on fresh-frozen Visiu...

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Autores principales: Chen, Limin, Chang, Darwin, Tandukar, Bishal, Deivendran, Delahny, Pozniak, Joanna, Cruz-Pacheco, Noel, Cho, Raymond J., Cheng, Jeffrey, Yeh, Iwei, Marine, Chris, Bastian, Boris C., Ji, Andrew L., Shain, A. Hunter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Method
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10688493/
https://www.ncbi.nlm.nih.gov/pubmed/38037084
http://dx.doi.org/10.1186/s13059-023-03121-6
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author Chen, Limin
Chang, Darwin
Tandukar, Bishal
Deivendran, Delahny
Pozniak, Joanna
Cruz-Pacheco, Noel
Cho, Raymond J.
Cheng, Jeffrey
Yeh, Iwei
Marine, Chris
Bastian, Boris C.
Ji, Andrew L.
Shain, A. Hunter
author_facet Chen, Limin
Chang, Darwin
Tandukar, Bishal
Deivendran, Delahny
Pozniak, Joanna
Cruz-Pacheco, Noel
Cho, Raymond J.
Cheng, Jeffrey
Yeh, Iwei
Marine, Chris
Bastian, Boris C.
Ji, Andrew L.
Shain, A. Hunter
author_sort Chen, Limin
collection PubMed
description Spatial transcriptomic technologies, such as the Visium platform, measure gene expression in different regions of tissues. Here, we describe new software, STmut, to visualize somatic point mutations, allelic imbalance, and copy number alterations in Visium data. STmut is tested on fresh-frozen Visium data, formalin-fixed paraffin-embedded (FFPE) Visium data, and tumors with and without matching DNA sequencing data. Copy number is inferred on all conditions, but the chemistry of the FFPE platform does not permit analyses of single nucleotide variants. Taken together, we propose solutions to add the genetic dimension to spatial transcriptomic data and describe the limitations of different datatypes. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-023-03121-6.
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spelling pubmed-106884932023-11-30 STmut: a framework for visualizing somatic alterations in spatial transcriptomics data of cancer Chen, Limin Chang, Darwin Tandukar, Bishal Deivendran, Delahny Pozniak, Joanna Cruz-Pacheco, Noel Cho, Raymond J. Cheng, Jeffrey Yeh, Iwei Marine, Chris Bastian, Boris C. Ji, Andrew L. Shain, A. Hunter Genome Biol Method Spatial transcriptomic technologies, such as the Visium platform, measure gene expression in different regions of tissues. Here, we describe new software, STmut, to visualize somatic point mutations, allelic imbalance, and copy number alterations in Visium data. STmut is tested on fresh-frozen Visium data, formalin-fixed paraffin-embedded (FFPE) Visium data, and tumors with and without matching DNA sequencing data. Copy number is inferred on all conditions, but the chemistry of the FFPE platform does not permit analyses of single nucleotide variants. Taken together, we propose solutions to add the genetic dimension to spatial transcriptomic data and describe the limitations of different datatypes. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-023-03121-6. BioMed Central 2023-11-30 /pmc/articles/PMC10688493/ /pubmed/38037084 http://dx.doi.org/10.1186/s13059-023-03121-6 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Method
Chen, Limin
Chang, Darwin
Tandukar, Bishal
Deivendran, Delahny
Pozniak, Joanna
Cruz-Pacheco, Noel
Cho, Raymond J.
Cheng, Jeffrey
Yeh, Iwei
Marine, Chris
Bastian, Boris C.
Ji, Andrew L.
Shain, A. Hunter
STmut: a framework for visualizing somatic alterations in spatial transcriptomics data of cancer
title STmut: a framework for visualizing somatic alterations in spatial transcriptomics data of cancer
title_full STmut: a framework for visualizing somatic alterations in spatial transcriptomics data of cancer
title_fullStr STmut: a framework for visualizing somatic alterations in spatial transcriptomics data of cancer
title_full_unstemmed STmut: a framework for visualizing somatic alterations in spatial transcriptomics data of cancer
title_short STmut: a framework for visualizing somatic alterations in spatial transcriptomics data of cancer
title_sort stmut: a framework for visualizing somatic alterations in spatial transcriptomics data of cancer
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10688493/
https://www.ncbi.nlm.nih.gov/pubmed/38037084
http://dx.doi.org/10.1186/s13059-023-03121-6
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