config_analysis.json

{
    # Moltraits
    "MOLTRAITS_ID_COL": "phenotype",
    "MOLTRAITS_SAMPLE_START": 7, # 0-indexed

    # Covariates
    "COVARIATES": ["sex", "age"],
    "COVARIATES_REFERENCES": [
      "sex::M"
    ],
    "COVARIATES_MEAN_IMPUTE": ["age"],

    # Covariance matrices
    "MATRICES": {
      "genetic": "data/matrices/genetic_matrix.tsv.gz",
      "phenotypic": "data/matrices/pheno_vectors.tsv.gz"
    },
    "MATRICES_TRANSFORM_DATAFRAMES": ["phenotypic"],

    # PEER factor analysis:
    # If `PEER_N_FACTORS` has NA, pipeline will skip PEER and include covariates
    # directly in LIMIX model. For factors>=0, pipeline will adjust coviariates using PEER.
    "PEER_N_FACTORS": ["NA", 0, 5],
    "PEER_ITERATIONS": 1000,
    "PEER_ACCOUNT_MEAN": "False",
    "PEER_INVERSE_NORMALIZE": "True",

    # For VarDecomp
    # If 'True', use PEER residuals as covariates
    # If 'False', use PEER factors as covariates
    "PEER_USE_RESIDUALS": true,

    # Variance Decomposition settings
    "VARDEC_NORMALIZATION": ["NA", "rank_normal"], # Use NA to denote no normalization
    "VARDEC_RESIDUAL_DISTRIBUTION" : ["normal", "bernoulli"],
    "VARDEC_MATRICES": {
      "Gen_Pheno": ["genetic", "phenotypic"],
      "Gen": ["genetic"]
    }
}