Goistrat: gene-of-interest-based sample stratification for the evaluation of functional differences
Our comprehensive approach provides a novel tool to identify disease-relevant functions of genes of interest (GOI) in large datasets. This integrated approach offers a valuable framework for understanding the role of the expression variation of a GOI in complex diseases and for informing on targeted therapeutic strategies.
Authors
- Jessica Kalla (ORCID: https://orcid.org/0000-0002-0196-4659)
- Gabriel Wasinger (ORCID: https://orcid.org/0000-0002-0323-7180)
- Carlos Uziel Pérez Malla (ORCID: https://orcid.org/0000-0003-0057-3223)
- Kilian Kluge (ORCID: https://orcid.org/0000-0002-4224-7314)
- Raheleh Sheibani‐Tezerji (ORCID: https://orcid.org/0000-0002-1025-646X)
- Gerda Egger (ORCID: https://orcid.org/0000-0003-2489-155X)
- Andreas Tiefenbacher (ORCID: https://orcid.org/0000-0001-7410-6164)
Institutions
- Ludwig Boltzmann Gesellschaft (AT)
- Comprehensive Cancer Center Vienna (AT)
- Christian Doppler Laboratory for Thermoelectricity (AT)
- Ludwig Boltzmann Institute Applied Diagnostics (AT)
- Medical University of Vienna (AT)
Publication Details
- Journal
- BMC Bioinformatics
- Published
- 2025-04-05
- DOI
- https://doi.org/10.1186/s12859-025-06109-0
- Primary Topic
- Prostate Cancer Treatment and Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Austrian Science Fund