Voelkl, Dennis and Mensching-Buhr, Malte and Sterr, Thomas and Bolz, Sarah and Schaefer, Andreas and Seifert, Nicole and Tauschke, Jana and Rayford, Austin and Straume, Oddbjorn and Zacharias, Helena U. and Grellscheid, Sushma Nagaraja and Beissbarth, Tim and Altenbuchinger, Michael and Goertler, Franziska (2025) HIDE: hierarchical cell-type deconvolution. BIOINFORMATICS, 41 (suppl1). i207-i216. ISSN 1367-4803, 1367-4811
Full text not available from this repository. (Request a copy)Abstract
Motivation Cell-type deconvolution is a computational approach to infer cellular distributions from bulk transcriptomics data. Several methods have been proposed, each with its own advantages and disadvantages. Reference based approaches make use of archetypic transcriptomic profiles representing individual cell types. Those reference profiles are ideally chosen such that the observed bulks can be reconstructed as a linear combination thereof. This strategy, however, ignores the fact that cellular populations arise through the process of cellular differentiation, which entails the gradual emergence of cell groups with diverse morphological and functional characteristics.Results Here, we propose Hierarchical cell-type Deconvolution (HIDE), a cell-type deconvolution approach which incorporates a cell hierarchy for improved performance and interpretability. This is achieved by a hierarchical procedure that preserves estimates of major cell populations while inferring their respective subpopulations. We show in simulation studies that this procedure produces more reliable and more consistent results than other state-of-the-art approaches. Finally, we provide an example application of HIDE to explore breast cancer specimens from TCGA.Availability and implementation A python implementation of HIDE is available at zenodo (doi: 10.5281/zenodo.14724906).
| Item Type: | Article |
|---|---|
| Subjects: | 500 Science > 530 Physics 500 Science > 570 Life sciences |
| Divisions: | Physics > Institute of Theroretical Physics > Chair Professor Schäfer > Group Andreas Schäfer Biology, Preclinical Medicine > Institut für Anatomie > Lehrstuhl für Humananatomie und Embryologie |
| Depositing User: | Dr. Gernot Deinzer |
| Date Deposited: | 22 Apr 2026 04:50 |
| Last Modified: | 22 Apr 2026 04:50 |
| URI: | https://pred.uni-regensburg.de/id/eprint/66956 |
Actions (login required)
 |
View Item |
