This dissertation focuses on the analysis of RNA-Seq data in the context of cancer, ultimately leading to the identification of candidate genes to target for downstream analysis of their role in cell transformation and oncogenesis. Chapter 1 is a review of the current research being done with retinoblastoma deficient cancer, and the current bioinformatics solutions available for the analysis of high throughput sequence data, which will aid in molecular classification of tumor entities and in the identification of candidate genes to target for downstream analysis. Chapter 2 describes transcriptome analysis of a zebrafish RB1-primitive neuroectodermal tumor model as well as a zebrafish RB1 homozygous mutant. It begins with an introduction to the experimental design and background on both the tumor model and RB1 homozygous mutant. It then goes into the data analysis and biological interpretation of the results, from alignment of the raw reads to pathway analysis and identification of candidate genes that drive tumorigenesis. Chapter 3 of the dissertation is attributed to a candidate gene discovered in the transcriptome analysis done in chapter 2, Chromodomain-helicase-DNA-binding protein 7 (CHD7). It focuses on generating a somatic phenotype and ultimately the generation of germline mutants for genetic analysis into the role of CHD7 in normal brain development. Chapter 4 is independent of the previous two chapters, and describes the development of software to map Sleeping Beauty Transposon integration sites in the zebrafish genome. It starts off with an introduction to the Sleeping Beauty Transposon, then focuses on the filtering of the raw read data generated from the sequencing of transposon junction fragments and the pipeline that maps the transposon insertion sites to the genome, ending with molecular verification of an insertion site via PCR and sequencing. The Appendix contains all supplementary information for Chapters 3-4.