Remm Score

The <strong>Re</strong>gulatory <strong>M</strong>endelian <strong>M</strong>utation (ReMM) score was created for relevance prediction of non-coding variations (SNVs and small InDels) in the human genome (hg19) in terms of Mendelian diseases. <strong>Usage</strong> The ReMM score is genome position wise (nucleotide changes are neglected). We precomputed all positions in the human genome (hg19 release) and stored the values in a tabix file (1-based). The scores ranging from 0 (non-deleterious) to 1 (deleterious). If you want to use the ReMM score together with the Genomiser, please have a look at the Exomiser framework manual <strong>ReMM score changelog</strong> 0.3.1: Bugfix of region chr17:79759050-81195210. Region is missing in older versions. 0.3: First official public version. Values for positions in training data are computed by cytoband-aware 10 fold cross-validation. Other position scores are compted by a generalized model of all training data. This version was used in the Genomiser publication (Smeley et.al. A Whole-Genome Analysis Framework for Effective Identification of Pathogenic Regulatory Variants in Mendelian Disease. AHJG. 2016)**调控孟德尔突变（Regulatory Mendelian Mutation，ReMM）评分**旨在针对孟德尔遗传病场景，对人类基因组（hg19版本）内的非编码变异（单核苷酸变异Single Nucleotide Variant, SNVs与小插入缺失Insertion-Deletion, InDels）开展相关性预测。 **使用说明** ReMM评分以基因组位置为计算维度，不考虑核苷酸的具体变化。我们已预先完成人类基因组（hg19版本）所有位点的评分计算，并将结果存储于采用1-based坐标体系的tabix格式文件中。评分取值范围为0（非有害）至1（有害）。 若需将ReMM评分与Genomiser工具配合使用，请参考Exomiser框架手册。 **ReMM评分更新日志** 0.3.1： 修复了chr17:79759050-81195210区域的相关问题，该区域在旧版本中存在缺失。 0.3： 首个正式公开版本。 训练数据内的位点评分通过基于细胞遗传学条带（cytoband）的10折交叉验证计算得到；其余位点的评分则基于全部训练数据构建的泛化模型计算得出。该版本已应用于Genomiser相关研究（Smeley 等. 《全基因组分析框架可有效鉴定孟德尔疾病致病调控变异》, 美国人类遗传学杂志(AHJG), 2016）