Association testing using pretrained DeepRVAT models

For using the pretrained DeepRVAT model provided as part of the package, or a custom pretrained model, we have setup pipelines for running only the association testing stage. This includes creating the association dataset files, computing gene impairment scores, regression, and evaluation.

Important note: DeepRVAT currently supports association testing using REGENIE or SEAK. Because REGENIE is actively maintained and gives better control for ancestry effects, as well as other aspects of genetic background, association testing with SEAK is deprecated and will be removed in a future version. Note especially that for binary phenotypes, REGENIE must be used.

Association testing with REGENIE

For specifics on input files and options for REGENIE steps 1 and 2, please refer to the REGENIE documentation.

Configuration and input files

Configuration parameters must be specified in deeprvat_input_pretrained_models_config.yaml. For details on the meanings of the parameters and the format of input files, see here.

For an example, refer to this configuration file, which includes REGENIE-specific parameters for steps 1 and 2. Importantly, specify

regenie_options:
  regenie_exp: True
  gtf_file: path/to/annotation_file.gtf.gz

To use pretrained models, you must specify use_pretrained_models: True in your deeprvat_input_pretrained_models_config.yaml configuration file. Additionally, provide the path to pretrained models (an output of the training pipeline) in the parameter pretrained_model_path. Within the pretrained_model_path directory, there must be a config.yaml file in that directory with the following set of specified keys that were used for training the pretrained models; rare_variant_annotations, training_data_thresholds, and model . See example file.

Below outlines the configuration parameters specified in deeprvat_input_pretrained_models_config.yaml.

The following parameters specify the locations of required input files:

gt_filename
variant_filename
phenotype_filename
annotation_filename
gene_filename

These parameters specify options for running DeepRVAT. Those marked (optional) have default values; see here for details.

phenotypes_for_association_testing
covariates
n_repeats
evaluation
y_transformation (optional)
association_testing_data_thresholds (optional)
cv_options (optional)

Note that the file specified by annotation_filename must contain a column corresponding to each annotation in the list rare_variant_annotations from deeprvat/pretrained_models/model_config.yaml.

You can set any parameter explained in the REGENIE documentation via the config. Most importantly, for association testing of binary traits use --bt in Step 2. For imbalanced traits, we also recommend Firth logistic regression:

step_2:
        options:
            - "--bt"
            - "--firth --approx --pThresh 0.01"

For quantitative traits:

step_2:
        options:
            - "--qt"

Run DeepRVAT gene impairment scoring followed by REGENIE

cd experiment
ln -s [path_to_deeprvat]/pretrained_models
snakemake -j 1 --snakefile [path_to_deeprvat]/pipelines/association_testing_pretrained.snakefile

Association testing with SEAK

Configuration file

Follow the instructions as above, but specify

regenie_options:
  regenie_exp: False

For an example, see this configuration file (rename or link it to deeprvat_input_pretrained_models_config.yaml in your working directory).

Executing the pipeline

snakemake -j 1 --snakefile [path_to_deeprvat]/pipelines/association_testing_pretrained.snakefile

Replace [path_to_deeprvat] with the path to your copy of the DeepRVAT repository.