一周小结 时间： 2013 年 8 月 23 日

DNA 甲基化检测的方法 大体分为两个步骤 : (1) 待检测样品的前期处理 (2) 目标序列的定位和甲基化状态的量化 亚硫酸氢钠 限制性内切酶 利用特定抗体对甲基化的胞 嘧啶进行免疫沉淀反应

Classification of Individual Lung Cancer Cell Lines Based on DNA Methylation Markers 时间： 2004 年 期刊： ournal of Molecular Diagnostics 分区：二区 影响因子： 主要内容： utility of linear discriminant analysis and artificial neural networks as classificatory tools of DNA methylation profiles, in an effort to develop diagnostic models that could distinguish SCLC from NSCLC

step: The percentage methylated refer-ence (PMR) for each locus was calculated by dividing the GENE:reference ratio of a sample by the GENE:reference ratio of highly methylatedSssI- treated human sperm DNA and multiplying by 100. utility of linear discriminant analysis and artificial neural networks The PMR data from 20 loci was subjected to backward step- wise analysis to eliminate the variables

CpG_MPs: identification of CpG methylation patterns of genomic regions from high-throughput bisulfite sequencing data 时间： 2013 年 期刊： Nucleic Acids Research 分区：二区 影响因子： 主要内容： developed a comprehensive tool, CpG_MPs, for identification and analysis of the methylation patterns of genomic regions from bisulfite sequencing data.

Workflow

Calculation of the methylation level of CpGs hotspot extension algorithm (i) unmethylated CpGs withmethylation levels <0.3 (ii) partially unmethylated CpGs ranging from 0.3 to 0.5 (iii) partially methylated CpGs ranging from 0.5 to 0.7 (iv) methylated CpGs whose methylation levels>0.7

Step 1: Convert the normalized methylation level of CpGs into the methylation status of CpGs. Step 2: Scan CpGs from a 5' to3' direction to extract the genomic regions including at least n successively unmethylated (methylated) CpGs as unmethylated (methylated) hotspots. Step 3: Extend the unmethylated (methylated) hotspots upstream and downstream to incorporate unmethylated (methylated) or partially unmethylated (methy-lated) CpGs into the hotspots as unmethylated regions, until methylated (unmethylated) or partially methylated (unmethylated) CpGs are met. Step 4: Combine two neighboring genomic regions with the same methylatio pattern together if their distance is <200 bp. Step 5: Compute the mean value and standard deviation of methylation level of CpGs in each unmethylated/methylated region

Identification of CMRs and DMRs

calculate the sample-methylation patterns of overlapping regions (ORs) in the reference genome are recorded defined to deter-mine the methylation patterns of ORs across multiple samples assess the overlapping ratio of the number of samples

Sequence features of genomic regions of different methylation patterns length, GC content and CpG ratio