1. 所有的方法都将FPR控制在5%以下;2. 由于TP的召回率由于样本数而提升,DESeq、DESeq2和edgeR在1CPM组中的FPR保持在0左右,而TP偏低;3. 在两重复情况下,edgeR在1CPM(10%,20%,50%和100%平均差)能有~25%的TP,而在其他两组中edgeR能有40%的TP而FPR只上升了~3%;4. DESeq和DESeq2对FPR控制的最好,...
1. 所有的方法都将FPR控制在5%以下;2. 由于TP的召回率由于样本数而提升,DESeq、DESeq2和edgeR在1CPM组中的FPR保持在0左右,而TP偏低;3. 在两重复情况下,edgeR在1CPM(10%,20%,50%和100%平均差)能有~25%的TP,而在其他两组中edgeR能有40%的TP而FPR只上升了~3%;4. DESeq和DESeq2对FPR控制的最好,...
Differential analysis of ATAC-seq shares many similarities with differential expression analysis of RNA-seq data. However, the distribution of ATAC-seq signal intensity is different from that of RNA-seq data, and higher sensitivity is required for DARs identification. Many different tools can be ...
最后,Cicero在用户定义的距离内的每对可及peak之间提供了一个介于-1到1之间的“Cicero可及性”分数,数值越大表示可及性越高。 此外,Cicero包提供了一个扩展工具包,用于使用Monocle 3提供的框架分析单细胞ATAC-seq实验。概述了使用Cicero的单细胞ATAC-Seq分析工作流程。 Cicero可以执行两种主要类型的分析: 构建和分析...
differential perform differential analysis based on footprints of two conditions plotting generate plots based on input training train Hidden Markov models estimation estimate sequence specific bias evaluation evaluate the predicted footprints based on ChIP-seq ...
至于Peak differential analysis 目前没有针对 ATAC-seq 专门开发的工具,对于那些借鉴 RNA-seq 差异基因分析的工具/方法,考虑到峰形状和分布也是非常重要的差异信息,作者认为如果有工具能够包含这点,应该能取得更好的结果。 Peak annotation 取得峰后进行 feature 注释,像基因、外显子、5'UTR、3'UTR等等。注释后也...
Performing the differential analysis dbObj<-dba.analyze(dbObj,method=DBA_DESEQ2) 默认使用DESeq2进行计算,可以选择DBA_EDGER(edgR),或者两个都要DBA_ALL_METHODS 韦恩图绘制 >dba.plotVenn(dbObj, mask=dbObj$masks$nt) mask是用于选择哪些样本用于绘图。
Differential analysis of ATAC-seq shares many similarities with differential expression analysis of RNA-seq data. However, the distribution of ATAC-seq signal intensity is different from that of RNA-seq data, and higher sensitivity is required for DARs identification. Many different tools can be ...
nfcore/atacseq is a bioinformatics analysis pipeline used for ATAC-seq data. The pipeline is built using Nextflow, a workflow tool to run tasks across multiple compute infrastructures in a very portable manner. It uses Docker/Singularity containers making installation trivial and results highly reprod...
calling小结第三部分——高级分析PeaksPeak differential analysisPeak annotationMotifsMotif database and scanMotif enrichment and activity analysisFootprintsDe novo toolsMotif-centric tools对于footprint分析的评价Nucleosome positioning第四部分——多组学数据联合分析建立调控网络结构与ChIP-seq联合分析与RNA-seq联合分析...