I developed a Python program to generate synthetic promoter sequences with specific characteristics to simulate and study promoter regulation. The project aimed to help in understanding how different motifs within a promoter region influence transcription.
For this project, I conducted a comprehensive RNA-seq data analysis to explore gene expression differences between experimental groups. First, I carried out quality control checks on the raw sequencing data to assess read quality, using tools such as Rsubread to extract quality scores and visualize them with boxplots. This step ensured that the data was of sufficient quality for reliable downstream analysis.