在使用annotatePeakInBatch进行注释时,默认查找距离peak最近的基因,也可以修改output的值,overlapping代表与peak区域存在overlap的基因,设置成这个值之后就会将与peak区间存在overlap的基因作为关联基因了,此外还有多种取值,适用不同条件,具体可以参考函数的帮助文档。 5...
在使用annotatePeakInBatch进行注释时,默认查找距离peak最近的基因,也可以修改output的值,overlapping代表与peak区域存在overlap的基因,设置成这个值之后就会将与peak区间存在overlap的基因作为关联基因了,此外还有多种取值,适用不同条件,具体可以参考函数的帮助文档。 5. 进行peak关联基因的富集分析 进行完基因注释之,得到pe...
library(TxDb.Hsapiens.UCSC.hg19.knownGene)aCR<-assignChromosomeRegion(overlaps,nucleotideLevel=FALSE,precedence=c("Promoters","immediateDownstream","fiveUTRs","threeUTRs","Exons","Introns"),TxDb=TxDb.Hsapiens.UCSC.hg19.knownGene)barplot(aCR$percentage,las=3) 欢迎关注我们的公众号～_～ 我们是两个农...
复制 library(TxDb.Hsapiens.UCSC.hg19.knownGene)aCR<-assignChromosomeRegion(sampleA,nucleotideLevel=FALSE,precedence=c("Promoters","immediateDownstream","fiveUTRs","threeUTRs","Exons","Introns"),TxDb=TxDb.Hsapiens.UCSC.hg19.knownGene)barplot(aCR$percentage,las=3) 输出结果如下所示 然后进行peak关联基...
library(TxDb.Hsapiens.UCSC.hg19.knownGene)aCR<-assignChromosomeRegion(sampleA, nucleotideLevel=FALSE, precedence=c("Promoters","immediateDownstream","fiveUTRs","threeUTRs","Exons","Introns"), TxDb=TxDb.Hsapiens.UCSC.hg19.knownGene)barplot(aCR$percentage, las=3) ...
library(TxDb.Hsapiens.UCSC.hg19.knownGene)aCR<-assignChromosomeRegion(sampleA,nucleotideLevel=FALSE,precedence=c("Promoters","immediateDownstream","fiveUTRs","threeUTRs","Exons","Introns"),TxDb=TxDb.Hsapiens.UCSC.hg19.knownGene)barplot(aCR$percentage,las=3) ...
barplot(aCR$percentage, las=3) 输出结果如下所示 然后进行peak关联基因的注释,用法如下 # 准备基因组注释信息 library(EnsDb.Hsapiens.v75) annoData <- toGRanges(EnsDb.Hsapiens.v75, feature="gene") # 进行 overlaps.anno <- annotatePeakInBatch(sampleA, ...
barplot(aCR$percentage, las=3) 输出结果如下所示 然后进行peak关联基因的注释,用法如下 # 准备基因组注释信息 library(EnsDb.Hsapiens.v75) annoData <- toGRanges(EnsDb.Hsapiens.v75, feature="gene") # 进行 overlaps.anno <- annotatePeakInBatch(sampleA, ...
barplot(aCR$percentage, las=3) 输出结果如下所示 然后进行peak关联基因的注释,用法如下 # 准备基因组注释信息 library(EnsDb.Hsapiens.v75) annoData <- toGRanges(EnsDb.Hsapiens.v75, feature="gene") # 进行 overlaps.anno <- annotatePeakInBatch(sampleA, ...