Chapter title |
Quantitative Proteomics for Xenopus Embryos II, Data Analysis
|
---|---|
Chapter number | 14 |
Book title |
Xenopus
|
Published in |
Methods in molecular biology, January 2018
|
DOI | 10.1007/978-1-4939-8784-9_14 |
Pubmed ID | |
Book ISBNs |
978-1-4939-8783-2, 978-1-4939-8784-9
|
Authors |
Sonnett, Matthew, Gupta, Meera, Nguyen, Thao, Wühr, Martin, Matthew Sonnett, Meera Gupta, Thao Nguyen, Martin Wühr |
Abstract |
The oocytes, embryos, and cell-free lysates of the frog Xenopus laevis have emerged as powerful models for quantitative proteomic experiments. In the accompanying paper (Chapter 13) we describe how to prepare samples and acquire multiplexed proteomics spectra from those. As an illustrative example we use a 10-stage developmental time series from the egg to stage 35 (just before hatching). Here, we outline how to convert the ~700,000 acquired mass spectra from this time series into protein expression dynamics for ~9000 proteins. We first outline a preliminary quality-control analysis to discover any errors that occurred during sample preparation. We discuss how peptide and protein identification error rates are controlled, and how peptide and protein species are quantified. Our analysis relies on the freely available MaxQuant proteomics pipeline. Finally, we demonstrate how to start interpreting this large dataset by clustering and gene-set enrichment analysis. |
X Demographics
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 4 | 57% |
Switzerland | 1 | 14% |
Unknown | 2 | 29% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 4 | 57% |
Scientists | 3 | 43% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 21 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 6 | 29% |
Professor | 3 | 14% |
Researcher | 2 | 10% |
Student > Postgraduate | 2 | 10% |
Student > Master | 2 | 10% |
Other | 3 | 14% |
Unknown | 3 | 14% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 9 | 43% |
Agricultural and Biological Sciences | 4 | 19% |
Chemistry | 2 | 10% |
Pharmacology, Toxicology and Pharmaceutical Science | 1 | 5% |
Immunology and Microbiology | 1 | 5% |
Other | 1 | 5% |
Unknown | 3 | 14% |