Modified: 2017-06-15 07:02:28
Compiled: Thu Jun 15 07:02:43 2017

Abstract In this workflow, we will use R/Bioconductor packages to explore, process, visualise and understand mass spectrometry-based proteomics data, starting with raw data, and proceeding with identification and quantitation data, discussing some of their peculiarities compared to sequencing data along the way. The workflow is aimed at a beginner to intermediate level, such as, for example, seasoned R users who want to get started with mass spectrometry and proteomics, or proteomics practitioners who want to familiarise themselves with R and Bioconductor infrastructure.

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1 Introduction

CSAMA 2017 Some part of this workshop require online access. The most bandwidth expensive operations are files downloads. Please copy the files from the local network and place them in your working directory1 If you are not sure what your working directory is, type getwd() or ask a helper.. This will stop them from being downloaded again.

Before we start:

If you identify typos, if there are parts that you would like to see expended or clarified, please let me know by telling me directly (during workshops), opening a github issue or by emailing me directly. Please do also briefly specify your background/familiarity with mass spectrometry and/or proteomics (beginner, intermediate or expert) so that I can update accordingly.

In recent years, there we have seen an increase in the number of packages to analyse mass spectrometry and proteomics data for R and Bioconductor, as well as an increase in total number of downloads.

Number of packages