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ATHENA: analysis of tumor heterogeneity from spatial omics measurements
SUMMARY: Tumor heterogeneity has emerged as a fundamental property of most human cancers, with broad implications for diagnosis and treatment. Recently, spatial omics have enabled spatial tumor profiling, however computational resources that exploit the measurements to quantify tumor heterogeneity i...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9154280/ https://www.ncbi.nlm.nih.gov/pubmed/35485743 http://dx.doi.org/10.1093/bioinformatics/btac303 |
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author | Martinelli, Adriano Luca Rapsomaniki, Maria Anna |
author_facet | Martinelli, Adriano Luca Rapsomaniki, Maria Anna |
author_sort | Martinelli, Adriano Luca |
collection | PubMed |
description | SUMMARY: Tumor heterogeneity has emerged as a fundamental property of most human cancers, with broad implications for diagnosis and treatment. Recently, spatial omics have enabled spatial tumor profiling, however computational resources that exploit the measurements to quantify tumor heterogeneity in a spatially aware manner are largely missing. We present ATHENA (Analysis of Tumor HEterogeNeity from spAtial omics measurements), a computational framework that facilitates the visualization, processing and analysis of tumor heterogeneity from spatial omics measurements. ATHENA uses graph representations of tumors and bundles together a large collection of established and novel heterogeneity scores that quantify different aspects of the complexity of tumor ecosystems. AVAILABILITY AND IMPLEMENTATION: ATHENA is available as a Python package under an open-source license at: https://github.com/AI4SCR/ATHENA. Detailed documentation and step-by-step tutorials with example datasets are also available at: https://ai4scr.github.io/ATHENA/. The data presented in this article are publicly available on Figshare at https://figshare.com/articles/dataset/zurich_pkl/19617642/2. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-9154280 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-91542802022-06-04 ATHENA: analysis of tumor heterogeneity from spatial omics measurements Martinelli, Adriano Luca Rapsomaniki, Maria Anna Bioinformatics Applications Notes SUMMARY: Tumor heterogeneity has emerged as a fundamental property of most human cancers, with broad implications for diagnosis and treatment. Recently, spatial omics have enabled spatial tumor profiling, however computational resources that exploit the measurements to quantify tumor heterogeneity in a spatially aware manner are largely missing. We present ATHENA (Analysis of Tumor HEterogeNeity from spAtial omics measurements), a computational framework that facilitates the visualization, processing and analysis of tumor heterogeneity from spatial omics measurements. ATHENA uses graph representations of tumors and bundles together a large collection of established and novel heterogeneity scores that quantify different aspects of the complexity of tumor ecosystems. AVAILABILITY AND IMPLEMENTATION: ATHENA is available as a Python package under an open-source license at: https://github.com/AI4SCR/ATHENA. Detailed documentation and step-by-step tutorials with example datasets are also available at: https://ai4scr.github.io/ATHENA/. The data presented in this article are publicly available on Figshare at https://figshare.com/articles/dataset/zurich_pkl/19617642/2. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2022-04-29 /pmc/articles/PMC9154280/ /pubmed/35485743 http://dx.doi.org/10.1093/bioinformatics/btac303 Text en © The Author(s) 2022. Published by Oxford University Press. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Applications Notes Martinelli, Adriano Luca Rapsomaniki, Maria Anna ATHENA: analysis of tumor heterogeneity from spatial omics measurements |
title | ATHENA: analysis of tumor heterogeneity from spatial omics measurements |
title_full | ATHENA: analysis of tumor heterogeneity from spatial omics measurements |
title_fullStr | ATHENA: analysis of tumor heterogeneity from spatial omics measurements |
title_full_unstemmed | ATHENA: analysis of tumor heterogeneity from spatial omics measurements |
title_short | ATHENA: analysis of tumor heterogeneity from spatial omics measurements |
title_sort | athena: analysis of tumor heterogeneity from spatial omics measurements |
topic | Applications Notes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9154280/ https://www.ncbi.nlm.nih.gov/pubmed/35485743 http://dx.doi.org/10.1093/bioinformatics/btac303 |
work_keys_str_mv | AT martinelliadrianoluca athenaanalysisoftumorheterogeneityfromspatialomicsmeasurements AT rapsomanikimariaanna athenaanalysisoftumorheterogeneityfromspatialomicsmeasurements |