GenixRL Scores Database: Pre-computed Variant Pathogenicity Scores from dbNSFP (BayesDel, ClinPred, MetaRNN)

This dataset provides pre-computed pathogenicity scores for genomic variants, specifically designed for use with the GenixRL (https://github.com/shabbas313/GenixRL). The database is derived from dbNSFP (dbNSFP5.2a_grch38.gz) and includes scores from key predictors: BayesDel_noAF, BayesDel_addAF, ClinPred, and MetaRNN. Dataset Contents genixrl_scores_db.tsv.gz: Compressed TSV file containing variant annotations with columns for chromosome, position, reference allele, alternate allele, and scores (BayesDel_noAF_score, BayesDel_addAF_score, ClinPred_score, MetaRNN_score). The file is tab-separated and gzip-compressed for efficiency. genixrl_scores_db.tsv.gz.tbi: Tabix index file for fast querying of the TSV using tools like pysam in Python. Methods and GenerationThe database was generated by querying dbNSFP (a comprehensive database of non-synonymous functional predictions) for a curated set of variants relevant to the GenixRL model. Scores were extracted for the following predictors: BayesDel_noAF and BayesDel_addAF: Bayesian deleteriousness scores for missense variants. ClinPred: Clinical predictor score for pathogenic potential. MetaRNN: Meta-ensemble RNN score for variant pathogenicity. Normalization is applied in the GenixRL model: BayesDel scores are scaled to [0,1] using min=-1.29334 and max=0.75731. Missing values are imputed using training medians from the associated model artifacts.本数据集为基因组变异提供预计算的致病性评分，专为配合GenixRL工具（https://github.com/shabbas313/GenixRL）使用而设计。 该数据库源自dbNSFP（dbNSFP5.2a_grch38.gz），包含多个核心预测工具的评分：BayesDel_noAF、BayesDel_addAF、ClinPred及MetaRNN。 ### 数据集内容 `genixrl_scores_db.tsv.gz`：经gzip压缩的制表符分隔值（TSV）文件，存储变异注释信息，列字段包括染色体、基因组位点、参考等位基因、变异等位基因及各类评分（BayesDel_noAF_score、BayesDel_addAF_score、ClinPred_score、MetaRNN_score）。该文件采用制表符分隔格式并经过gzip压缩，以提升存储与传输效率。 `genixrl_scores_db.tsv.gz.tbi`：Tabix索引文件，可通过Python的pysam等工具实现TSV文件的快速查询。 ### 方法与生成流程 本数据库通过针对与GenixRL模型相关的精选变异集查询dbNSFP（一款全面的非同义突变功能预测数据库）构建而成。 随后提取以下预测工具的评分： - BayesDel_noAF与BayesDel_addAF：错义突变的贝叶斯有害性评分 - ClinPred：评估变异致病潜力的临床预测评分 - MetaRNN：用于变异致病性评估的元集成循环神经网络评分 GenixRL模型已对评分实施归一化处理：BayesDel评分通过设定最小值min=-1.29334、最大值max=0.75731，被缩放至[0,1]区间。缺失值通过关联模型工件中的训练集中位数进行插补。