As one of my first research areas in Olga Vitek’s lab, I worked on developing MSstatsPTM, a statistical tool for quantitative mass spectrometry-based proteomics. The package is used to detect differentially abundant post-translational modifications (PTMs). It does this through feature summarization, fitting a linear mixed effects model, and removing confounding with overall protein level. The package is designed to be used by proteomic researchers so it must be easy to implement without extensive experience in computer science. More details on the work can be seen in the poster below. This project is currently in the process of being published.
MSstatsPTM US HUPO 2021 poster. I presented this work in a short lightning talk presentation, as well as a longer open form poster session.