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tRigon: an R package and Shiny App for integrative (path-)omics data analysis.
Hölscher, David L; Goedertier, Michael; Klinkhammer, Barbara M; Droste, Patrick; Costa, Ivan G; Boor, Peter; Bülow, Roman D.
Afiliación
  • Hölscher DL; Institute of Pathology, RWTH Aachen University Clinic, Aachen, Germany.
  • Goedertier M; Department of Nephrology and Immunology, RWTH Aachen University Clinic, Aachen, Germany.
  • Klinkhammer BM; Institute of Pathology, RWTH Aachen University Clinic, Aachen, Germany.
  • Droste P; Institute for Computational Genomics, RWTH Aachen University Clinic, Aachen, Germany.
  • Costa IG; Institute of Pathology, RWTH Aachen University Clinic, Aachen, Germany.
  • Boor P; Institute of Pathology, RWTH Aachen University Clinic, Aachen, Germany.
  • Bülow RD; Department of Nephrology and Immunology, RWTH Aachen University Clinic, Aachen, Germany.
BMC Bioinformatics ; 25(1): 98, 2024 Mar 05.
Article en En | MEDLINE | ID: mdl-38443821
ABSTRACT

BACKGROUND:

Pathomics facilitates automated, reproducible and precise histopathology analysis and morphological phenotyping. Similar to molecular omics, pathomics datasets are high-dimensional, but also face large outlier variability and inherent data missingness, making quick and comprehensible data analysis challenging. To facilitate pathomics data analysis and interpretation as well as support a broad implementation we developed tRigon (Toolbox foR InteGrative (path-)Omics data aNalysis), a Shiny application for fast, comprehensive and reproducible pathomics analysis.

RESULTS:

tRigon is available via the CRAN repository ( https//cran.r-project.org/web/packages/tRigon ) with its source code available on GitLab ( https//git-ce.rwth-aachen.de/labooratory-ai/trigon ). The tRigon package can be installed locally and its application can be executed from the R console via the command 'tRigonrun_tRigon()'. Alternatively, the application is hosted online and can be accessed at https//labooratory.shinyapps.io/tRigon . We show fast computation of small, medium and large datasets in a low- and high-performance hardware setting, indicating broad applicability of tRigon.

CONCLUSIONS:

tRigon allows researchers without coding abilities to perform exploratory feature analyses of pathomics and non-pathomics datasets on their own using a variety of hardware.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Aplicaciones Móviles Idioma: En Revista: BMC Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2024 Tipo del documento: Article País de afiliación: Alemania

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Aplicaciones Móviles Idioma: En Revista: BMC Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2024 Tipo del documento: Article País de afiliación: Alemania