- In this report, I will analyse a publicly available dataset based on clinical breast cancer data. Breast cancer is the most diagnosed cancer in women. There are several subtypes of diseases characterized by different genetic drivers for cancer risk and tumour growth. The human epidermal growth factor receptor 2 amplified (HER2: ERBB2 / ERBB2IP) breast cancer is one of the most aggressive subtypes. In addition, I will investigate HER3 (ERBB3), HER4 (ERBB4), PIK3C2B, MDM4, LRRN2, NFASC, KLHDC8A, and CDK18 gene mutations. Although there are targeted therapies that have been developed to treat these cancer cases, the response rate ranges from 40% - 50%. I will download, decompress, clean and process the TCGA RNASeq data for breast cancer from cbioportal and identify the differentially expressed genes between ERBB2 / ERBB2IP, ERBB3, ERBB4, PIK3C2B, MDM4, LRRN2, NFASC, KLHDC8A, and CDK18 cancer tumours.
- The dataset can be downloaded from this link
Run All Code Chunks in assignment-2.qmd from RStudio project & render to PDF or HTML
- See full report in html or pdf format at: Full Report