Computer Science Graduate Seminar

Wednesday, August 10, 2022, 2:00pm

Computational Method for Single-cell ATAC-seq Imputation and Dimensionality Reduction

  • Herr Zhijian Li , M.Sc. – Institute for Computational Genomics
  • Place: Raum 5053.2 (großer B-IT-Raum)/Informatikzentrum, Ahornstraße 55



Single-cell sequencing assay for transposase-accessible chromatin (scATAC-seq) allows mapping of regulatory variation of thousands of cells at the single-cell resolution. However, analyzing the scATAC-seq data is computationally challenging due to the sparsity, high dimensionality, and the nature of the binary signal. In this thesis, we proposed scOpen, a computational approach for quantification of single-cell open chromatin status and reduction of the dimensionality based on the non-negative matrix factorization (NMF) topic modeling. We demonstrated that scOpen can improve several crucial downstream analysis steps of scATAC-seq, such as clustering, visualization, cis-regulatory DNA interactions, and delineation of regulatory features. We also applied scOpen to investigate the regulatory programs that drive the development of chronic kidney disease (CKD). Altogether, these results demonstrate that scOpen is a useful computational approach in single-cell open chromatin data analysis.


The computer science lecturers invite interested people to join.