Variant-level odds ratios for 18 phenotypes

This dataset is from the paper "Extracting and calibrating evidence of variant pathogenicity from population biobank data", which evaluates the broad potential of using population cohort data as evidence of pathogenicity in variant assessment. The dataset contains variant-level odds ratios in 18 phenotypes spanning 41 genes, calculated using case data from 469,803 UK Biobank participants. These odds ratios can be used as PS4 (population) evidence of pathogenicity within the ACMG/AMP variant interpretation framework using the calibrated thresholds provided in Table 2 (for specific phenotypes), Supplementary Table 5 (for specific genes), or Table 3 (overall).medRxiv preprint: https://www.medrxiv.org/content/10.1101/2024.08.14.24311911v2We share odds ratio data by phenotype, yielding 18 files. Each file has the following columns:<b>gene:</b> Gene in which the variant is located (e.g., <i>LDLR</i>)<b>variant:</b> Variant in chr-pos-ref-alt format (e.g., 11-108227661-C-T)<b>odds_estimate:</b> Odds ratio that measures disease (i.e., phenotype) enrichment for the variant<b>odds_lower:</b> Odds ratio 95% confidence lower bound<b>odds_upper:</b> odds ratio 95% confidence upper bound<b>revel_score:</b> REVEL score for the variant, obtained via the Variant Effect Predictor (VEP)<b>clinvar_status:</b> Variant ClinVar status (one of "P/LP", "B/LB", "VUS", or "Absent")Note that not all variants listed have associated odds ratios. Typically comprising the majority of variants, this is because for many variants, all participants with the variant don't have the associated disease. If there are not enough such participants, a corrected odds ratio will be a distorted measure. See the "Calculating variant-level odds ratios from population cohort data" section of the methods for more information. If an odds ratio could not be calculated for a variant, the "odds_estimate", "odds_lower", and "odds_upper" columns have the sentinel value "-".

本数据集源自论文《从人群生物银行数据中提取并校准变异致病性证据》（Extracting and calibrating evidence of variant pathogenicity from population biobank data），该研究评估了将人群队列数据用作变异致病性评估证据的广泛应用潜力。
本数据集包含覆盖41个基因的18种表型的变异级比值比（odds ratio），该指标基于469803名英国生物银行（UK Biobank）参与者的病例数据计算得到。

上述比值比可结合论文表2（针对特定表型）、补充表5（针对特定基因）或表3（整体校准阈值），在美国医学遗传学与基因组学学会/分子病理学协会（ACMG/AMP）变异解读框架中作为PS4（人群）致病性证据使用。本研究成果以预印本形式发布于medRxiv，链接为：https://www.medrxiv.org/content/10.1101/2024.08.14.24311911v2。

本研究按表型分类共享比值比数据集，共生成18个数据文件。每个文件包含以下列：
<b>gene：基因</b>：变异所在基因（例如<i>LDLR</i>）
<b>variant：变异</b>：采用chr-pos-ref-alt格式标注的变异（例如11-108227661-C-T）
<b>odds_estimate：比值比估计值</b>：用于衡量该变异对应的疾病（即目标表型）富集程度的比值比
<b>odds_lower：比值比95%置信下限</b>：比值比95%置信区间的下限值
<b>odds_upper：比值比95%置信上限</b>：比值比95%置信区间的上限值
<b>revel_score：REVEL评分（REVEL score）</b>：该变异的REVEL评分，通过变异效应预测器（Variant Effect Predictor, VEP）获取
<b>clinvar_status：ClinVar状态</b>：变异的ClinVar标注状态，可选值为"P/LP"（致病/可能致病）、"B/LB"（良性/可能良性）、"VUS"（意义未明变异）或"Absent"（未收录）

需要注意的是，并非所有列出的变异均配有对应的比值比数据，此类变异通常占全部列出变异的多数。究其原因是许多携带该变异的参与者并未罹患对应疾病，若携带变异的患病人数不足，校正后的比值比将成为失真的衡量指标。更多细节请参见论文方法部分的“从人群队列数据计算变异级比值比”章节。若无法为某一变异计算比值比，则其`odds_estimate`、`odds_lower`及`odds_upper`列将以哨兵值`"-"`填充。