R

You can use Kipoi from R via the reticulate package. For a more complete example, see https://github.com/kipoi/kipoi/blob/master/notebooks/R-api.ipynb.

Installation

1. Install Kipoi. See how
2. Install R
3. Install the reticulate package. From R, run: install.packages("reticulate")

Make sure reticulate is using python from the miniconda/anaconda installation (same as Kipoi):

library(reticulate)
reticulate::py_config()

Usage

Use a specific conda environment

library(reticulate)
reticulate::use_condaenv("kipoi-Basset)

or install the dependencies from R:

kipoi$install_model_requirements("Basset")

Get the model:

kipoi <- import('kipoi')
model <- kipoi$get_model('Basset')

Make a prediction for example files

predictions <- model$pipeline$predict_example()

Use dataloader and model separately

# Get the dataloader
setwd('~/.kipoi/models/Basset')
dl <- model$default_dataloader(intervals_file='example_files/intervals.bed', fasta_file='example_files/hg38_chr22.fa')
# get a batch iterator
it <- dl$batch_iter(batch_size=4)
# predict for a batch
batch <- iter_next(it)
model$predict_on_batch(batch$inputs)

Make predictions for custom files directly:

pred <- model$pipeline$predict(dl_kwargs, batch_size=4)