# #——包括= FALSE --------------------------------------------------------- knitr: opts_chunk美元集(崩溃= TRUE ) ## ----------------------------------------------------------------------------- # 数据加载file_counts < -执行(“extdata / vignette_counts.txt”、包=“regsplice”)< -读取的数据。table(file_counts, header = TRUE, sep = "\t"， stringsAsFactors = FALSE) head(data) #提取计数，gene_IDs和n_exons计数<- data[， 2:7] tbl_exons <- table(sapply(strsplit(data$exon， ":")， function(s) s[[1]])) gene_IDs <- names(tbl_exons) n_exons <- unname(tbl_exons) dim(counts) length(gene_IDs) head(gene_IDs) length(n_exons) sum(n_exons) #创建条件vector条件<- rep(c("未处理"，"已处理")，每个= 3)条件 ## ----------------------------------------------------------------------------- 库(regsplice) rs_data < - RegspliceData(计数,gene_IDs、n_exons条件)rs_results < - suppressWarnings (regsplice (rs_data,种子= 123 )) ## ----------------------------------------------------------------------------- summaryTable (rs_results ) ## ----------------------------------------------------------------------------- 库(regsplice) rs_data < RegspliceData (gene_IDs计数,n_exons,条件 ) ## ----------------------------------------------------------------------------- rs_data < - filterZeros (rs_data ) ## ----------------------------------------------------------------------------- rs_data < - filterLowCounts (rs_data ) ## ----------------------------------------------------------------------------- rs_data < - runNormalization (rs_data ) ## ----------------------------------------------------------------------------- rs_data < - runVoom (rs_data) #视图列元数据包括正常化和规范化库大小colData (rs_data因素 ) ## ----------------------------------------------------------------------------- rs_results < - initializeResults (rs_data ) ## ----------------------------------------------------------------------------- # 为再现性随机种子种子< - 123 #适合正规化模型rs_results < - suppressWarnings (fitRegMultiple (rs_results rs_data,种子=种子))#适合零模型rs_results < fitNullMultiple (rs_results,rs_data、种子=种子)#适合“完整”模型(不需要如果' when_null_selected =“的”在下一步)rs_results < - fitFullMultiple (rs_results rs_data,种子=种子 ) ## ----------------------------------------------------------------------------- rs_results < - LRTests (rs_results ) ## ----------------------------------------------------------------------------- summaryTable (rs_results ) ## ----------------------------------------------------------------------------- summaryTable (rs_resultsn =正 ) ## ----------------------------------------------------------------------------- sum (p_adj (rs_results) < 0.05)表(p_adj (rs_results) < 0.05 ) ## ----------------------------------------------------------------------------- # 负载真正DS状态标签file_truth < -执行(“extdata / vignette_truth.txt”、包=“regsplice”)data_truth < -阅读。表(file_truth头= TRUE, 9 =“t \”,stringsAsFactors = FALSE) str基因(data_truth) #删除过程中过滤regsplice分析data_truth < - data_truth [data_truth基因% % gene_IDs美元(rs_results)]暗(data_truth)长度(gene_IDs (rs_results)) #真正的DS基因数量在模拟数据集(data_truth ds_status = = 1美元)和表(data_truth ds_status美元)#列联表比较真实和预测DS地位对于每个基因#(意义阈值:罗斯福< 0.05)表(真实= data_truth ds_status美元,预测= p_adj (rs_results) < 0.05) #增加阈值检测的基因,以牺牲更多的假阳性表(真实= data_truth ds_status美元,预测= p_adj (rs_results) < 0.99 ) ## ----------------------------------------------------------------------------- # 基因外显子3 # 4生物样本; 2 samples in each of 2 conditions design_example <- createDesignMatrix(condition = rep(c(0, 1), each = 2), n_exons = 3) design_example