DEG-PI: A Computational Tool that Identifies Differentially Expressed Genes and Enriched Pathways in Cancer Tissues
Cancer is a devastating disease affecting millions of people. It is caused by mutations in DNA that causes cells to grow uncontrollably in the body forming tumors. Bladder cancer is a common cancer being the tenth most diagnosed in 2020 with approximately 570,000 new cases. There are specific risk factors that increase the risk of developing bladder cancer. Some of these include gender, age, smoking, and occupational hazards such as aromatic amines exposure. Since there are a variety of different genetic and environmental causes of bladder cancer, further research has been done to try to identify differnetially expressed genes and enriched pathways. A differentially expressed gene (DEG) is a gene whose expression level is different in cancer tissue than normal tissue. An enriched pathway is a biological pathway that contains a statistically significant number of DEGs compared to what would be expected by chance. DEG-PI uses both R and Python to identify DEGS and enriched pathways in cancer tissue.
In order to run make sure to have the following Python libraries installed:
streamlit, pandas, plotly.express, PIL
In order to run make sure to have the follwoing R libraries installed:
GEOquery, limma, umap, tidyverse, WebGestaltR