def summarize_results(results, gene, holdout_cancer_type, signal, z_dim,
                      seed, algorithm, data_type):
    """
    Given an input results file, summarize and output all pertinent files

    Arguments
    ---------
    results: a results object output from `get_threshold_metrics`
    gene: the gene being predicted
    holdout_cancer_type: the cancer type being used as holdout data
    signal: the signal of interest
    z_dim: the internal bottleneck dimension of the compression model
    seed: the seed used to compress the data
    algorithm: the algorithm used to compress the data
    data_type: the type of data (either training, testing, or cv)
    """
    results_append_list = [
        gene,
        holdout_cancer_type,
        signal,
        z_dim,
        seed,
        algorithm,
        data_type,
    ]

    metrics_out_ = [results["auroc"], results["aupr"]] + results_append_list

    roc_df_ = results["roc_df"]
    pr_df_ = results["pr_df"]

    roc_df_ = roc_df_.assign(
        predictor=gene,
        signal=signal,
        z_dim=z_dim,
        seed=seed,
        algorithm=algorithm,
        data_type=data_type,
    )

    pr_df_ = pr_df_.assign(
        predictor=gene,
        signal=signal,
        z_dim=z_dim,
        seed=seed,
        algorithm=algorithm,
        data_type=data_type,
    )

    return metrics_out_, roc_df_, pr_df_