https://github.com/pwilmart/smith_spc_2018

A large-scale spectral counting data analysis using PAW pipeline, edgeR, R, and Jupyter notebooks
https://github.com/pwilmart/smith_spc_2018

edger jupyter-notebooks paw-pipeline proteomics r spectral-counting statistical-analysis

Last synced: about 2 months ago
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A large-scale spectral counting data analysis using PAW pipeline, edgeR, R, and Jupyter notebooks

• Host: GitHub
• URL: https://github.com/pwilmart/smith_spc_2018
• Owner: pwilmart
• License: mit
• Created: 2019-02-12T02:53:07.000Z (almost 6 years ago)
• Default Branch: master
• Last Pushed: 2019-09-06T17:27:29.000Z (over 5 years ago)
• Last Synced: 2024-10-11T15:49:12.185Z (3 months ago)
• Topics: edger, jupyter-notebooks, paw-pipeline, proteomics, r, spectral-counting, statistical-analysis
• Language: Jupyter Notebook
• Size: 20.3 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Smith_SpC_2018

A large-scale spectral counting data analysis using PAW pipeline, edgeR, R, and Jupyter notebooks.

### Phil Wilmarth, OHSU

#### February 2019

The data is from a [recent study](https://www.sciencedirect.com/science/article/pii/S0002939418301193) where human retinal and choroidal endothelial cells were compared. The study was 5 donor eyes where retinal and choroidal cells were collected and cultured in a paired design. The cell lysates from each of the 10 cell cultures were profiled using large-scale separations with a fast-scanning linear ion trap. There were about half a million MS2 scans per sample for a dataset size of a little over 5 million. The data are available at the PRIDE archive ([PXD005972](https://www.ebi.ac.uk/pride/archive/projects/PXD005972)).

There is a direct link to the rendered [notebook HTML file](https://pwilmart.github.io/TMT_analysis_examples/Smith_2018_edgeR.html).

---

A few relevant files from the archive are present in the repository:

- analysis_overview.pptx - summary of the data analysis steps

- quant_protein_summary_8.txt - a grouped protein summary file

- edgeR_input.txt - data extracted from results file for edgeR analysis

- edgeR_results.txt - statistical testing results

- HCEC_HREC_quant_protein_summary_sprot.xlsx - final summary sheet

  - proteomics data from quant_protein_summary_8.txt

  - statistical results from edgeR

  - extra protein annotations