slides, R Shiny application
Proteomics Data Analysis (PDA)
Mass spectrometry based proteomic experiments generate ever larger datasets and, as a consequence, complex data interpretation challenges. This course focuses on the statistical concepts for peptide identification, quantification, and differential analysis. Moreover, more advanced experimental designs and blocking will also be introduced. The core focus will be on shotgun proteomics data, and quantification using label-free precursor peptide (MS1) ion intensities. The course will rely exclusively on free and userfriendly opensource tools in R/Bioconductor. The course will provide a solid basis for beginners, but will also bring new perspectives to those already familiar with standard data interpretation procedures in proteomics.
Students can sharpen their background knowledge on Mass Spectrometry, Proteomics & Bioinformatics for Proteomics here: Mass Spectrometry and Bioinformatics for Proteomics
Licence: Creative Commons Attribution Share Alike 4.0 International
Contact: https://statomics.github.io/pages/about.html
Keywords: proteomics, quantitative proteomics
Target audience: biologists, bioinformaticians
Resource type: slides, R Shiny application
Status: Active
Prerequisites:
Note, that users who develop R/markdown scripts can access data both from the web or from disk within their scripts. So they do not need to download the data first. The msqrob2gui Shiny App only works with data that is available on disk.
More information on our tools can be found in our papers (L. J. Goeminne, Gevaert, and Clement 2016), (L. J. E. Goeminne et al. 2020) and (Sticker et al. 2020). Please refer to our work when using our tools.
Scientific topics: Proteomics
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