Analysing Mutational Pathways of Skin in Cancerous Patients

As a volunteer research assistant at Thomas Jefferson University, I contributed to the Cancer Genomics and Bioinformatics Core under the guidance of Professor Paolo Fortina. My work focused on developing and optimizing pipelines for post-sequencing genomic data analysis, with the ultimate goal of offering advanced analytical services to internal researchers and compete with external vendors. This involved comparing Illumina DRAGEN Apps and Open Source Software solutions for secondary analysis, as well as implementing mutation signature analysis using SigProfiler, a tool based on non-negative matrix factorization (NMF), to identify patterns in DNA nucleotide changes and infer the causes of cancer. I had the responsiblity of ensuring the robustness of pipelines, translating between data models to help researches in using the software of their own preference for analysis, and ensure fast turnaround of secondary analysis.

Project Overview

• Duration: September 2023 – Present (Ongoing)
• Technologies and Tools: Python, SigProfiler (NMF-based mutation signature analysis), Python, bcftools, samtools, pyvcf, Illumina DRAGEN Apps
• Skills Developed: Genomic Analysis, Skill2
• Data Formats: FASTQ, BAM, vcf
• Visualization: Matplotlib, SigProfiler plotting tools

Conclusion

I made contributions to advancing cancer genomics research through the development of robust pipelines for DNA mapping, variant calling, and mutation signature analysis. By leveraging tools like Illumina DRAGEN Apps and SigProfiler, I enabled researchers to gain deeper insights into the mutational pathways of cancer, supporting the development of cancer identification and mechanism understanding. The skills and experience gained in this role, including critical appraisal of statistical methods, large-scale data analysis, and scientific communication.