Browsing by Subject "eQTL analysis"

High-grade serous carcinoma (HGSC) is a highly lethal cancer type characterised by high genomic instability and frequent copy number alterations. This study examines the relationships between genetic variants in tumour germline and gene expression levels to obtain a better understanding of gene regulation in HGSC. This would then improve knowledge of the cancer mechanisms in order to find, for example, potential new treatment targets and biomarkers. The aim is to find significantly associated variant-gene pairs in HGSC. Expression quantitative trait loci (eQTL) analysis is a well-suited method to explore these associations. eQTL analysis is a suitable approach to analysing also those variants that are located in the non-coding genomic regions, as indicated by previous genome-wide association studies to contain many disease-linked germline variants. The current eQTL analysis methods are, however, not applicable for association testing between genes and variants in the context of HGSC because of the special genomic features of the cancer. Therefore, a new eQTL analysis approach, SegmentQTL, was developed for this study to accommodate the copy-number-driven nature of the disease. Careful input processing is of particular importance in eQTL as it has a notable effect on the number of significantly associated variant-gene pairs. It is also relevant to maintain adequate statistical power, which affects the reliability of the findings. In all, this study uses eQTL analysis to uncover variant-gene associations. This helps to improve knowledge of gene regulation mechanisms in HGSC in order to find new treatments. To apply the analysis to the HGSC data, a novel eQTL analysis method was developed. Additionally, appropriate input processing is important prior to running the analysis to ensure reliable results.