ATHENA: analysis of tumor heterogeneity from spatial omics measurements.
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.
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