The Effects of Sex Chromosome Complement Aware Read Mapping on Variant Calling in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a type of liver cancer common in Sub-Saharan Africa and South East Asian countries. Each year more than 700,000 new cases and more than 600,000 deaths are recorded worldwide due to HCC. According to the American Cancer Society HCC is ranked the 5th most common cancer worldwide with a male:female susceptibility ratio ranging between 2:1 and 8:1. HCC risk factors include lifestyle behaviors, such as persistent alcohol abuse and smoking, prolonged exposure to aflatoxins, chronic viral hepatitis infections, inherited metabolic diseases and non-alcoholic fatty liver diseases. To understand the genetic effects underlying sex-bias in HCC, it is necessary to include the sex chromosomes in genomics analyses. X and Y chromosomes are often discluded in genomics studies because of the technical and analytical challenges: sequence homology. The purpose of this thesis is to analyze the effects of sex chromosome complement aware read mapping to germline variant calling. 10 male and 10 female tumor adjacent samples from The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA LIHC) cohort were processed using sex-aware and default reference and the concordance of the two approaches was examined. We detected a higher disconcordance of 0.69% on variants called on the X chromosome and a disconcordance of 0.51% on variants called on the Y chromosomes for the reference and alternative alleles respectively compared to autosomes. Variants called on the REF/ALT genotypes had a disconcordances of 1.00%, 1.05%, 1.35% and 12.34% for the autosomes, chromosome 7, the X, and the Y chromosome, respectively. At the end of the project we concluded that the generated datasets showed the effect of sex-aware read mapping on variant calling. Though the data did not show the sites that can be called as variants in one dataset but not in the other, rather the concordance looked at sites that were called as variants in both data sets.