|Shadi Eshghi Ph.D. is an associate scientist in the biomarker development department at Genentech. Her work currently focuses on development of bioinformatics tools and techniques to facilitate analysis and interpretation of targeted mass spectrometry data. Prior to joining Genentech, Shadi worked in Dr. Hui Zhang’s group at Johns Hopkins University on development of novel computational and experimental methods for exploring the glycome and glycoproteome using mass spectrometry. Read More |
Her research led to development of GPQuest, a spectral library matching algorithm and accompanying application for identification of intact glycopeptides in complex biological matrices using LC-MS/MS. Shadi obtained a Ph.D. in biomedical engineering from Johns Hopkins University and a B.Sc. in electrical engineering.
A Workflow for Quality Assessment, Quantitation and Statistical Inference of Targeted Proteomics Data using Skyline and Panorama
Skyline and Panorama are integral parts of our data analysis and management system for targeted mass spectrometry experiments. Implemented as a module on the Labkey Server bioinformatics platform, Panorama enables integration of a diverse set of tools such as R programming to create customized workflows. Taking advantage of this feature, we are developing a workflow for post-processing of targeted mass spectrometry Skyline files on the Panorama server. This workflow combines built-in Panorama features with custom R packages (e.g. TargetedMSQC and MSstats) to perform quality control, quantitation and statistical inference. These tests can be performed on Skyline files within Panorama to create a comprehensive and sharable report. This workflow will provide an efficient means for high-throughput analysis of targeted mass spectrometry data, and enable sharing of not only files and final results, but also the processing steps required to generate reports, thus bringing more transparency to the data processing pipeline.