A computational framework for detecting low abundance clonal hematopoiesis mutations in large-scale tumor sequence datasets

This May, our webinar series features a talk by Dr. Vaidhyanathan Mahaganapathy, a computational biologist at the Ellison Institute for Transformative Medicine and a recent PhD graduate from the Khiabanian Lab of Rutgers University.

In this webinar, Dr. Mahaganapathy will summarize his work with Dr. Khiabanian’s group on developing the MERIT pipeline on the CGC. MERIT utilizes Samtools to identify all positions with alternate alleles from the aligned, indexed sequencing reads and then extracts additional information including alleles' depths, Phred quality, and position-in-read information for all variants. MERIT was originally developed by Mohammad Hadigol, but is updated and maintained by Viadhyanathan. He will speak about:

• Clonal hematopoiesis (CH), which is associated with inflammation, cardiovascular diseases, and a reduction in overall survival rate. 

• Building a computational pipeline that can reliably and reproducibly call low abundance somatic CH mutations, in pan-cancer primary tumor and matched normal blood exome sequencing samples from TCGA.

More about the speaker

Vaidhyanathan Mahaganapathy

Vaidhyanathan is a biotechnologist by training, who transitioned to a bioinformatician when he realized he could combine his passion for Biology with the puzzle-solving skills needed for scripting. During his dissertation, he explored different variant calling approaches on a variety of human genomic datasets and in the process developed skills for building, testing, and optimizing robust computational pipelines and workflows. In his current position at the Ellison Institute, he is working on establishing a sequence analysis toolbox for the different projects, and assisting on establishing a long-read sequencing protocol.

LinkedIn: linkedin.com/in/vaidhy-m