Nextflow workflow for deconvolution method development and benchmarking.
Author: Sean Maden
Acknowledgements: Hédia Tnani, Nick Eagles
Scripts provided in the sh and yml folders show which dependencies are required and
how to install them. For most runs, you will at minimum need a recent version of NextFlow,
R, and the nnls, SummarizedExperiment, and SingleCellExperiment libraries, with additional
required dependencies for other deconvolution methods besides the non-negative least
squares (NNLS) method.
You can use the provided .yml file to set up a conda virtual environment. From the top
level of r-nf_deconvolution, run the following:
conda env create -f ./yml/r-nf_deconvolution.yml
Activate the new environment with:
conda activate r-nf_deconvolution
You should now be ready to run nextflowr-deconvolution.
Example datasets are contained in the data folder. Several setup .R scripts are provided in the rscript
folder to download and prepare example data for a workflow run.
The lung adenocarcinoma dataset from sc_mixology (Tian et al 2019) can be downloaded and set up by running:
Rscript ./rscript/prepare_lung-adeno-example.R
Use a terminal to navigate to the top level of nextflowr-deconvolution and run the following:
sh ./sh/r-nf.sh
This should use example data to produce a series of outputs. The main outputs are stored at the top level in a .csv file called results_table_*.csv.