Study, detection and classification of cell cycle orbits along with circadian rhythm corresponding to different cell types in single cell data

All seminars are held at the Department of Automatic Control, in the seminar room M 3170-73 on the third floor in the M-building, unless stated otherwise.

Master Thesis presentation by Archana Mallick and Nguyen Duc Cuong

• Title:  Study, detection and classification of cell cycle orbits along with circadian rhythm corresponding to different cell types in single cell data
• Author: Archana Mallick and Nguyen Duc Cuong
• Date & Time: June 4th, 10:30–11:00
• Location: Seminar Room M 3170-73 in the M-building, LTH
• Supervisor: Anders Rantzer and David Ohlin
• Examiner:  Magnus Fontes

Abstract

Single-cell RNA sequencing (scRNA-seq) enables the study of how circadian rhythms interact with cell cycle progression at the level of individual cells. In this thesis, publicly available scRNA-seq data from healthy human bone marrow are used to analyze this relationship. Circadian phase is inferred for each cell based on the expression of core clock genes, and rhythmic genes are identified using harmonic modeling. Cell cycle activity is quantified using established S-phase and G2/M gene signatures, alongside a data-driven approach to identify additional phase-specific marker genes through differential expression analysis. This work also proposes a computational framework to identify and extend cell-cycle marker genes, providing deeper insight into temporal transcriptional regulation in the hematopoietic system and offering potential gene signatures for detecting abnormal proliferation and identifying tumor cells.