Bioinformatic analysis of single-cell genomesapplications in chronic lymphocytic leukemia

Abstract

Single-cell DNA sequencing (scDNA-seq) has the potential to transform our knowledge of genomic variation among somatic cells, including cancer onset, progression and treatment. However, scDNA-seq entails a complex pipeline with multiple potential biases. In this thesis, I provide a better understanding of the sources of technical noise in scDNA-seq datasets, in particular in relation to their relevance when carrying out comparative and evolutionary analyses of cell populations. In addition, I use scDNA-seq to illustrate how in chronic lymphocytic leukemia (CLL) more than one cell lineage can resist drug therapy, that multiple migrations can occur between the bone marrow and the blood, and how CLL cells might be dividing faster in the blood than in the bone marrow.