M.Sc. in Quantitative & Computational Biology, University of Trento, Italy
M.Sc. in Quantitative & Computational Biology, University of Trento, Italy
M.Sc. in Quantitative & Computational Biology, University of Trento, Italy
This project focuses on the analysis of RNA-seq count data derived from KIRP samples obtained from The Cancer Genome Atlas (TCGA). The goal is to explore the molecular differences between tumor and normal tissues through a comprehensive bioinformatics pipeline. Key steps include data preprocessing, filtering for protein-coding genes using the biomaRt package, and identifying DEGs via the edgeR package. Visualization techniques such as volcano plots and heatmaps are used to interpret the differential expression results. Gene set enrichment analysis (GSEA) is performed using the fgsea package to uncover significantly altered pathways in cancer. In addition, we investigate transcription factors (TFs) with enriched binding motifs in the promoters of regulated genes and examine protein-protein interaction (PPI) networks using STRING and igraph. This multi-layered approach provides insights into the transcriptional landscape of KIRP and highlights potential biomarkers or therapeutic targets for further research.