Short URL to this page: http://bit.ly/2016-rbiocprot-sun
- Introduction to R/RStudio
- R/Bioconductor for proteomics
- Data visualisation
mzRandMSnbasepackages for raw data- Identification data in
mzR,mzID,MSnID - The
MSnbasepackage:MSnSets for quantitative proteomics - Experimental designs: biological and technical variability, blocking and randomisation
- Handling missing values in proteomics data
- Differential expression of proteomics data (t-test for continuous
data, count data,
limma) - Multiple testing
- Wrap-up
| time | Tue.25.Oct | Wed.26.Oct | Thu.27.Oct |
|---|---|---|---|
| 9:00 - 10:00 | R/RStudio intro (LG) | Identification 1: DB Search and other methods (DT) | Advanced quant: Technology selection, Power, Biofluids (DT) |
| 10:00 - 11:00 | R (LG) | Practical (DT) | Bridget Calder, UCT, demos Skyline |
| 11:00 - 11:30 | Coffee | Coffee | Coffee |
| 11:30 - 12:30 | R/Bioconductor for proteomics (LG) | Identification 2: protein inference and controlling FDR (DT) | Missing values (lecture + demo/practical) (LG) |
| 12:30 - 13:30 | Lunch | Lunch | Lunch |
| 13:30 - 14:30 | MS data: pwiz and quameter (DT) | R/Bioconductor: mzR, mzID, MSnID (LG) | Differential expression (t-test for continuous data, count data, limma) (LG) |
| 14:30 - 15:30 | Data visualisation (LG) | Intro: quantitative proteomics (DT) | Multiple testing (LG) |
| 15:30 - 16:00 | Coffee | Coffee | Coffee |
| 16:00 - 17:00 | Practical with R: the mzR and MSnbase packages for raw data (LG) | The MSnbase package: MSnSets for quantitative proteomics (LG) | Wrap-up |
LG: Laurent Gatto - DT: David Tabb
-
Gatto L. and Christoforou A. Using R and Bioconductor for proteomics data analysis, Biochim Biophys Acta - Proteins and Proteomics, 2013. PMID:23692960 (preprint)
-
Gatto L, Breckels LM, Naake T, Gibb S. Visualisation of proteomics data using R and Bioconductor. Proteomics. 2015 Feb 18. doi: 10.1002/pmic.201400392. PMID:25690415.
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Gatto L. and Lilley K.S. MSnbase - an R/Bioconductor package for isobaric tagged mass spectrometry data visualisation, processing and quantitation, Bioinformatics, 28(2), 288-289, 2012 PMID:22113085
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