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ATHENA: analysis of tumor heterogeneity from spatial omics measurements.
Martinelli, Adriano Luca; Rapsomaniki, Maria Anna.
Afiliación
  • Martinelli AL; IBM Research Europe, Zurich, 8803 Rüschlikon, Switzerland.
  • Rapsomaniki MA; IBM Research Europe, Zurich, 8803 Rüschlikon, Switzerland.
Bioinformatics ; 38(11): 3151-3153, 2022 05 26.
Article en En | MEDLINE | ID: mdl-35485743
ABSTRACT

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.
Asunto(s)

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Biología Computacional / Neoplasias Límite: Humans Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2022 Tipo del documento: Article País de afiliación: Suiza

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Biología Computacional / Neoplasias Límite: Humans Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2022 Tipo del documento: Article País de afiliación: Suiza