ENCODE TF ChIP-seq data analysis

We downloaded 2,216 ChIP-seq experiment data from the ENCODE Project. The list of the data is in Supplementary Table S8. The data were lifted over from hg19 to hg38. We found overlapping peaks on four different categories: (1) 500bp upstream the promoter region of pcRNA-associated coding genes, (2) 500bp upstream promoter region of pcRNAs, (3) pcRNA genomic loci, and (4) pcRNA genomic loci but not overlapping with promoter region. To understand the correlation of TF binding patterns in the four categories, we made a binary matrix per category that consists of rows of TFs and columns of pcRNA/coding genes. Hence, the matrix contains connections between TF and pcRNA/associate coding genes. The matrix of category 2 is clustered by Euclidian Distance. To check the extent to which promoter sharing or proximity determines TFBS correlation, we also separated the clustered heat-map in the pcRNA bidirectional transcript (BIDIR) subgroup to the other subgroups (Non-BIDIR). To directly compare the TF binding patterns between each category, the other three matrices were sorted by the same order of the clustered matrix. We used the MatLab function corr2 to calculate r-value between category (1) and (2). We performed Monte Carlo simulation to calculate the p-value and test the significance of the r-value.

我们从ENCODE项目（ENCODE Project）中下载了2216条染色质免疫共沉淀测序（Chromatin Immunoprecipitation sequencing, ChIP-seq）实验数据集，该数据集的列表详见补充表S8。所有数据均已从hg19基因组版本转换至hg38基因组版本。我们在四类不同区域中鉴定到了重叠峰：(1) 与pcRNA相关的编码基因的启动子区域上游500bp区域；(2) pcRNA的启动子区域上游500bp区域；(3) pcRNA基因组位点；(4) 不与启动子区域重叠的pcRNA基因组位点。为探究四类区域中转录因子（Transcription Factor, TF）结合模式的相关性，我们为每一类区域构建了二值矩阵：矩阵行对应转录因子，列对应pcRNA/编码基因，因此该矩阵可体现转录因子与pcRNA/关联编码基因之间的结合关联。第二类区域的二值矩阵通过欧氏距离（Euclidean Distance）进行聚类。为验证启动子共享或邻近性对转录因子结合位点（Transcription Factor Binding Site, TFBS）相关性的影响程度，我们将聚类热图划分为pcRNA双向转录本（BIDIR）亚组与非双向转录本（Non-BIDIR）亚组分别分析。为直接对比不同类别间的转录因子结合模式，其余三类矩阵均按照该聚类矩阵的排序规则进行排序。我们使用MATLAB函数corr2计算了类别(1)与类别(2)之间的相关系数r值，并通过蒙特卡洛模拟计算了P值，对该相关系数r值的显著性进行检验。