An exploration of internal reference scaling (IRS) normalization in isobaric tagging proteomics experiments.
MIT License
An exploration of internal reference scaling (IRS) normalization in isobaric tagging proteomics experiments. Also, examples of how IRS-normalized data affects statistical testing, and how to avoid using ratios in the analyses.
The IRS method was first described in this publication:
Plubell, D.L., Wilmarth, P.A., Zhao, Y., Fenton, A.M., Minnier, J., Reddy, A.P., Klimek, J., Yang, X., David, L.L. and Pamir, N., 2017. Extended multiplexing of tandem mass tags (TMT) labeling reveals age and high fat diet specific proteome changes in mouse epididymal adipose tissue. Molecular & Cellular Proteomics, 16(5), pp.873-890.
The analysis is of a mouse lens development time course (6 points 3 days apart from E15 to P9) where three replicates of the time points were done in 3 separate TMT labelings. The lens is a unique system that has been studied for many years and the prior knowledge can be used to guide some analysis steps. The data is from this publication:
Khan, S.Y., Ali, M., Kabir, F., Renuse, S., Na, C.H., Talbot, C.C., Hackett, S.F. and Riazuddin, S.A., 2018. Proteome Profiling of Developing Murine Lens Through Mass Spectrometry. Investigative Ophthalmology & Visual Science, 59(1), pp.100-107.
Four jupyter notebook files (R kernel). If you click on the notebook files (*.ipynb extensions), they will render and display in your bowser. Please be patient as they can take a minute to render.
Data from Kahn, et al.:
Sample information for design matrix:
Saved results from the statisticl testing:
Added HTML renderings of the notebooks for those who just want to see the analysis steps and figures (these may load faster):
Added R scripts extracted from the notebooks. These can be used in RStudio or modified for your own analyses.