tRigon: an R package and Shiny App for integrative (path-)omics data analysis
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 comprehens...
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2024-03-01
|
| Series: | BMC Bioinformatics |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12859-024-05721-w |
| _version_ | 1797273054955438080 |
|---|---|
| author | David L. Hölscher Michael Goedertier Barbara M. Klinkhammer Patrick Droste Ivan G. Costa Peter Boor Roman D. Bülow |
| author_facet | David L. Hölscher Michael Goedertier Barbara M. Klinkhammer Patrick Droste Ivan G. Costa Peter Boor Roman D. Bülow |
| author_sort | David L. Hölscher |
| collection | DOAJ |
| description | 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 ‘tRigon::run_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. |
| first_indexed | 2024-03-07T14:38:03Z |
| format | Article |
| id | doaj.art-b0d0aa69d8504016b2e20a8120906e4d |
| institution | Directory Open Access Journal |
| issn | 1471-2105 |
| language | English |
| last_indexed | 2024-03-07T14:38:03Z |
| publishDate | 2024-03-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Bioinformatics |
| spelling | doaj.art-b0d0aa69d8504016b2e20a8120906e4d2024-03-05T20:31:36ZengBMCBMC Bioinformatics1471-21052024-03-0125111110.1186/s12859-024-05721-wtRigon: an R package and Shiny App for integrative (path-)omics data analysisDavid L. Hölscher0Michael Goedertier1Barbara M. Klinkhammer2Patrick Droste3Ivan G. Costa4Peter Boor5Roman D. Bülow6Institute of Pathology, RWTH Aachen University ClinicInstitute of Pathology, RWTH Aachen University ClinicInstitute of Pathology, RWTH Aachen University ClinicInstitute of Pathology, RWTH Aachen University ClinicInstitute for Computational Genomics, RWTH Aachen University ClinicInstitute of Pathology, RWTH Aachen University ClinicInstitute of Pathology, RWTH Aachen University ClinicAbstract 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 ‘tRigon::run_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.https://doi.org/10.1186/s12859-024-05721-wData explorationStatisticsUser interfacePathomics |
| spellingShingle | David L. Hölscher Michael Goedertier Barbara M. Klinkhammer Patrick Droste Ivan G. Costa Peter Boor Roman D. Bülow tRigon: an R package and Shiny App for integrative (path-)omics data analysis BMC Bioinformatics Data exploration Statistics User interface Pathomics |
| title | tRigon: an R package and Shiny App for integrative (path-)omics data analysis |
| title_full | tRigon: an R package and Shiny App for integrative (path-)omics data analysis |
| title_fullStr | tRigon: an R package and Shiny App for integrative (path-)omics data analysis |
| title_full_unstemmed | tRigon: an R package and Shiny App for integrative (path-)omics data analysis |
| title_short | tRigon: an R package and Shiny App for integrative (path-)omics data analysis |
| title_sort | trigon an r package and shiny app for integrative path omics data analysis |
| topic | Data exploration Statistics User interface Pathomics |
| url | https://doi.org/10.1186/s12859-024-05721-w |
| work_keys_str_mv | AT davidlholscher trigonanrpackageandshinyappforintegrativepathomicsdataanalysis AT michaelgoedertier trigonanrpackageandshinyappforintegrativepathomicsdataanalysis AT barbaramklinkhammer trigonanrpackageandshinyappforintegrativepathomicsdataanalysis AT patrickdroste trigonanrpackageandshinyappforintegrativepathomicsdataanalysis AT ivangcosta trigonanrpackageandshinyappforintegrativepathomicsdataanalysis AT peterboor trigonanrpackageandshinyappforintegrativepathomicsdataanalysis AT romandbulow trigonanrpackageandshinyappforintegrativepathomicsdataanalysis |