From 7d58426175806d89de5cc676fac82dc2ad1569a7 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Marcel=20M=C3=BCck?= Date: Mon, 26 Feb 2024 11:53:37 +0100 Subject: [PATCH] corrected corrupt sphinx docstring --- deeprvat/annotations/annotations.py | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-) diff --git a/deeprvat/annotations/annotations.py b/deeprvat/annotations/annotations.py index 0f7e98e7..c7eb0802 100644 --- a/deeprvat/annotations/annotations.py +++ b/deeprvat/annotations/annotations.py @@ -1086,16 +1086,16 @@ def deepripe_score_variant_onlyseq_all( Compute variant scores using a deep learning model for each specified variant. Parameters: - - model_group (dict): A dictionary containing deep learning models for different choices. Each entry should be a key-value pair, where the key is the choice name and the value is a tuple containing the model and additional information. - - variant_bed (list): A list of variant bedlines, where each bedline represents a variant. - - genomefasta (str): Path to the reference genome in FASTA format. - - seq_len (int, optional): The length of the sequence to use around each variant. Default is 200. - - batch_size (int, optional): Batch size for parallelization. Default is 1024. - - n_jobs (int, optional): Number of parallel jobs for processing variant bedlines. Default is 32. + - model_group (dict): A dictionary containing deep learning models for different choices. Each entry should be a key-value pair, where the key is the choice name and the value is a tuple containing the model and additional information. + - variant_bed (list): A list of variant bedlines, where each bedline represents a variant. + - genomefasta (str): Path to the reference genome in FASTA format. + - seq_len (int, optional): The length of the sequence to use around each variant. Default is 200. + - batch_size (int, optional): Batch size for parallelization. Default is 1024. + - n_jobs (int, optional): Number of parallel jobs for processing variant bedlines. Default is 32. Returns: - dict: A dictionary containing variant scores for each choice in the model_group. - Each entry has the choice name as the key and the corresponding scores as the value. + dict: A dictionary containing variant scores for each choice in the model_group. + Each entry has the choice name as the key and the corresponding scores as the value. """ predictions = {}