brianhill11 / kBET_testing

Code for testing kBET metric

kBET_testing

Code for testing kBET metric

Creating the Anaconda environment

To replicate the Anaconda environment, make sure conda is installed and then run this command:

conda env create -f environment.yml

Generating data

The generate_data.ipynb notebook contains code to generate single-cell data using datasets included in the scVI package. It creates data in 3 formats:

1. cells x genes matrix ("prefix".csv file)
2. genes x cells matrix ("prefix"_T.csv file)
3. cells x genes h5ad file ("prefix".h5ad)

Additionally, a cells x covariates file "prefix"_batch_labels.csv is created, where the first column is the batch label for each cell, and the second column is the predicted cell-type label for each cell.

Note that the code currently dumps dense matrices, which means for large datasets the files can be big and it can take a while to dump the data to disk. Also note that these matrices compress fairly well, so a future optimization could be to write them as compressed files, assuming the methods can read compresssed files.

Running Seurat

The R Seurat is installed using CRAN.

Running DCA

The DCA package is installed with conda.

Running scVI

The scVI package is installed with conda.

Running kBET

The kBET R package is installed from Github using the following commands:

library(devtools)
install_github('theislab/kBET')