This repository contains code for further development of the scaling normalization methods implemented in the scran package. It is based on the code at https://github.com/MarioniLab/Deconvolution2016, which accompanies the paper Pooling across cells to normalize single-cell RNA sequencing data with many zero counts by Lun et al. (2016).
First, install the helper package in package/ with:
R CMD INSTALL package/
... or some variant thereof. It is also worth running:
BiocManager::install(ask=FALSE, version="devel")
... to ensure that the latest versions of all relevant packages are installed.
To run the simulations, enter the simulations/ directory and run:
sim_noDE.R, which simulates a variety of scenarios involving no DE between populations.sim_biDE.R, which simulates a variety of scenarios involving DE between two populations.sim_multiDE.R, which simulates a variety of simulations involving DE between three populations.
Note that the parallelization framework assumes a SLURM cluster with the Rdevel command (to run a version of R with BioC-devel packages).
This can be changed by modifying createBatchParam.R in package/R and/or slurm.tmpl in package/inst/scripts.
To summarize the simulation results, run summarizer.R to cluster the simulation scenarios based on the pattern of errors across all methods.
To analyze real data, enter the real directory and run:
zeisel.Rmd, to compute size factors for the Zeisel brain data set.pbmc4k.Rmd, to compute size factors for the PBMC 4K data set.