Dresden 2026 – scientific programme

Parts | Days | Selection | Search | Updates | Downloads | Help

BP: Fachverband Biologische Physik

BP 15: Computational Biophysics III

BP 15.10: Talk

Wednesday, March 11, 2026, 12:15–12:30, BAR/SCHÖ

Adaptive Determination of Cluster Number in Single-Cell RNA-seq — •Cornelius Miller, Felix Wehrenberg, Dominik Egger, and Sophia Rudorf — Institute of Cell Biology and Biophysics, Leibniz University Hannover, Hannover, Germany

Single-cell RNA sequencing (scRNA-seq) has transformed transcriptomic research by enabling gene expression profiling at the resolution of individual cells. The complexity and high dimensionality of scRNA-seq data pose substantial challenges for effective data interpretation. Current analysis pipelines often struggle with computational scalability and the subjective nature of parameter selection. Here, we introduce a comprehensive Python-based framework that automates key analytical stages while maintaining user flexibility. A critical innovation of this framework is the implementation of an adaptive clustering algorithm designed to estimate cluster count without prior knowledge. This method was specifically developed to define the number of distinct subpopulations in Mesenchymal Stem Cell (MSC) datasets, where cellular heterogeneity is often ambiguous. Furthermore, by leveraging parallelization, the proposed architecture handles high-dimensional datasets with improved latency compared to sequential execution. This approach resolves common ambiguities in defining cell types, offering a robust tool for unbiased exploratory data analysis.

Keywords: Single-cell RNA-seq (scRNA-seq); Mesenchymal stem cells (MSC); Clustering