Abstract
This chapter guides the user through an analysis pipeline that includes preprocessing raw mass spectrometry data into a user-friendly quantitative protein report and statistical analysis. We use a publicly available dataset as a working example that covers two prominent strategies for mass spectrometry-based proteomics, the extensively used data-dependent acquisition (DDA) and the emerging data-independent acquisition (DIA) technology. We use MaxQuant for DDA data and Spectronaut for DIA data preprocessing. Both software packages are well-established tools in the field. We perform subsequent analysis in the R software environment which offers a large repertoire of tools for data analysis and visualization. The chapter will aid lab scientists with some familiarity with R to reproducibly analyze their experiments using state-of-the-art bioinformatics methods.
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Pham, T.V., Jimenez, C.R. (2019). Quantitative Analysis of Mass Spectrometry-Based Proteomics Data. In: Li, K. (eds) Neuroproteomics. Neuromethods, vol 146. Humana, New York, NY. https://doi.org/10.1007/978-1-4939-9662-9_12
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DOI: https://doi.org/10.1007/978-1-4939-9662-9_12
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