Zylatis / BrdU

Code for "Memory CD4 T cell subsets are kinetically heterogeneous and replenished from naive T cells at high levels"

Package for curve fitting and analysis of BrdU + Ki67 experimental data

G. H. Gossel 2016 [e-mail]

Repo contents

R files used as imports

• analysisHeaders.R
• formatOutput.R
• getBootSettings.R
• getData.R
• getFunctions.R
• getModelConfigs.R
• getODEs.R
• getODEsolver.R
• getSettings.R
• singleSetCI.R

R files run directly by user

• runBestFits.R
• runAnalysis.R
• runCombineBootData.R
• runBootstrap.R
• runExamine.R

Mathematica files used to prepare analytic expressions

• makeCfns.nb
• MakeRFunctions.nb

Raw data files

• 29AprilRegate.xlsx

Formatted data files

4Tem and 4Tcm versions of:

• 4TxxBRDU.xls
• 4TxxAllKi67Pos.xls
• 4TxxMeanKi67Pos.xls

Requirements

The following R packages are required

• iterators
• parallel
• doParallel
• foreach
• Rcpp
• xlsx*
• odeintr**
• gdata
• stats
• nleqslv
• deSolve
• fBasics
• GenSA
• ggplot2
• reshape
• gridExtra

• This can be difficult to get working because of rJava issues. See "rJavaNotes.txt" for more information.

** This is an in-development package. To resolve several issues, the most up to date (development) version from Github was used and can be found here: https://github.com/thk686/odeintr. In order to obtain this version directly from git via commandline, additional packages will be required (httr, git2r, curl, openssl)

Instructions

1. Modify workDir.R to reflect correct local package directory.

2. Modify getModelConfigs.R to define kBox/bBox min/max and desired source terms to loop over. For now one must use only configurations for which the ODE expressions already exist in Functions/ and CFunctions/. Further information on how to use the Mathematica files to generate further expressions will be forthcoming.

3. Run runBestFits.R using Rscript which takes command line arguments according to:

   Rscript runBestFits.R

   where the arguments are chosen from sets according to:

   cell - {4Tem, 4Tcm} source.switch -{immediate, delayStep} model - {kinHet, kinHetExtended, kinHetExtended2,tempHet} ncores - integer > 0

   Example: Rscript runBestFits.R 4Tem delayStep kinHet 64

   Note: There is no check to ensure the number of cores is reasonable, it is currently up to the user to ensure this for their machine.

4. Modify runAnalysis.R according to which source terms the user wants included in analysis by re-defining 'target.source.list'

5. Run Rscript runAnalysis.R . This will output the summary files for the best fits.

   Example: Rscript runAnalysis.R kinHet 4Tem delayStep

6. Run 'runBootstrap.R' with command line arguments for cell type, source switch function, sigma value, model, and number of cores

   Example: Rscript runBootStrap.R 4Tem delayStep 0.4 kinHet 64

   The above command will run the bootstrap code for the case where the source term is 40% of the memory pool per week. This presupposes the bestfits have been run for this source. It will automatically do the bootstraps on the 'best best-fit' box configuration available

7. Run 'runCombinedBootData.R' to collect all the bootstrap outputs into a useful form (CIs). This takes some time. Only takes three command line arguments, , , and