As part of my research in statistical analysis, I worked on developing MSstatsLiP, a tool for quantitative mass spectrometry-based proteomics. The package is used to detect differentially abundant peptides identified through Limited proteolysis-coupled mass spectrometry (LiP-MS). LiP-MS is a recently developed proteomics approach that identifies protein structural changes directly on a proteome-wide scale. Similarly to MSstatsPTM, this approach incorporates convolution with changes in the underlying global protein adjustment. Because of this I was able to leverage a large amount of previous work in creating this package. The general workflow is as follows: 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. This project is currently in the process of being published.