Biology subjects

Simeth, J.

Publications and source records attributed to Simeth, J..

2 recordsLinked to original sources

bioRxiv2025

Harp: Platform Independent Deconvolution Tool

MotivationThe cellular composition of a solid tissue can be assessed either through the physical dissociation of the tissue followed by single-cell analysis techniques or by computational deconvolution of bulk gene expression profiles. However, both approaches are prone to significant biases. Tissue dissociation often results in disproportionate cell loss, while deconvolution is hindered by biological and technological inconsistencies between the datasets it relies on. ResultsUsing calibration datasets that include both experimentally measured and deconvolution-based cell compositions, we present a new method, Harp, which reconciles these approaches to produce more reliable deconvolution results in applications where only gene expression data is available. Both on simulated and real data, harmonizing cell reference profiles proved advantageous over competing state-of-the-art deconvolution tools, overcoming technological and biological batch effects. Availability and ImplementationR package available at https://github.com/spang-lab/harp. Code for reproducing the results of this paper is available at https://github.com/spang-lab/harplication. ContactZahra.Nozari@klinik.uni-regensburg.de

bioinformatics↗

bioRxiv2023

Virtual Tissue Expression Analysis

MotivationBulk RNA expression data is widely accessible, whereas single-cell data is relatively scarce in comparison. However, single-cell data offers profound insights into the cellular composition of tissues and cell-type-specific gene regulation, both of which remain hidden in bulk expression analysis. ResultsHere, we present tissueResolver an algorithm designed to extract single-cell type information from bulk data, enabling us to attribute expression changes to individual cell types. The outcome is a virtual tissue that can be analyzed in a manner similar to single-cell RNA-seq data. When validated on simulated data tissueResolver outperforms competing methods. Additionally, our study demonstrates that tissueResolver reveals previously overlooked celltype specific regulatory distinctions between the activated B-cell-like (ABC) and germinal center B-cell-like (GCB) subtypes of diffuse large B-cell lymphomas (DLBCL). Availability and ImplementationR package available at https://github.com/spang-lab/tissueResolver. Code for reproducing the results of this paper is available at https://github.com/spang-lab/tissueResolver-docs. Contactjakob.simeth@klinik.uni-regensburg.de

bioinformatics↗