Proteomic Data Analysis: Strategies and Software Solutions
This GCB Academy session is designed as a complement to GCB Academy course "Fundamentals of Mass Spectrometry for Proteomic and Metabolomic Analyses" (Nov. 7) and GCB Academy course "Experimental Design: Get the most your of your proteome" (Nov. 8) and is intended for users of the Proteomics and Metabolomics Shared Resource who have or plan on generating LC/MS based Proteomic Datasets with the Shared Resource. This first portion of the course will focus on the effective use of Scaffold to characterize qualitative proteomic datasets. This will include an overview of Scaffold and features such as interpretation of spectral matches at a protein or peptide level, gene ontology classification, homology matching, spectral count data, and data export. The second portion of the course will cover common proteomic data analysis strategies from supplemental data (typically .xlsx file formats from Rosetta Elucidator) provided as part of the Shared Resource's quantitative proteomic workflows. This will include an overview of the typical features of a quantitative data return document, various data summarization levels, calculating peptide/protein relative fold-changes and p-values, exporting data for motif analysis (PTM specific datasets), and performing Principle Component Analysis (PCA) and 2D Clustering within JMP Pro.
Registration required: https://duke.qualtrics.com/jfe/form/SV_bKlpk6mFKRPRs69