# #——风格,回声= FALSE,结果= '飞机 '------------------------------------ BiocStyle::减价(css。= c(“custom.css文件 ')) ## ---- eval = FALSE -------------------------------------------------------------- # 如果(!requireNamespace("BiocManager"， quiet =TRUE)) # install.packages("BiocManager") ## BiocManager::install(c("EpiTxDb"，"EpiTxDb. hs .hg38")) ## ---- results="hide"， include=TRUE, message=FALSE，警告= FALSE -------------- 库(EpiTxDb)库(EpiTxDb.Hs.hg38 ) ## ----------------------------------------------------------------------------- etdb etdb < - EpiTxDb.Hs.hg38.snoRNAdb () ## ----------------------------------------------------------------------------- keytypes (etdb)列(etdb)头(键(etdb“MODID”))选择(etdb键=“1”,列= c(“MODNAME”、“MODTYPE”、“MODSTART”、“MODSTRAND”、“SNNAME”、“RXGENENAME”、“SPECTYPE”、“SPECGENENAME”),keytype = " MODID ") ## ----------------------------------------------------------------------------- 物种(etdb)有机体(etdb) seqlevels (etdb ) ## ----------------------------------------------------------------------------- 修改(etdb、列= c(“mod_id”、“mod_type”,“mod_name”、“rx_genename”、“spec_genename”、“ref_type”、“ref”),过滤器=列表(mod_id = 1:3 )) ## ----------------------------------------------------------------------------- # 分离序列的名字,通常是一个接收标识符modificationsBy(etdb, by = "seqnames") #分割修改类型modificationsBy(etdb, by = "seqnames")=“modtype ") ## ---- 回声= FALSE ------------------------------------------------------------ suppressPackageStartupMessages({库(TxDb.Hsapiens.UCSC.hg38.knownGene)库(BSgenome.Hsapiens.UCSC.hg38 ) }) ## ---- eval = FALSE ------------------------------------------------------------ # 库(TxDb.Hsapiens.UCSC.hg38.knownGene) #库(BSgenome.Hsapiens.UCSC.hg38 ) ## ----------------------------------------------------------------------------- txdb < - TxDb.Hsapiens.UCSC.hg38。knownGene seqlevels(txdb) <- "chr1" bs <- BSgenome.Hsapiens.UCSC. bsgenome。tx hg38 etdb < - EpiTxDb.Hs.hg38.RMBase () < - exonsBy (txdb)国防部< -修改(etdb过滤器=列表(sn_name =“chr1”))长度(mod ) ## ----------------------------------------------------------------------------- mod_tx < - shiftGenomicToTranscript (mod,tx) (mod_tx长度 ) ## ----------------------------------------------------------------------------- mod_tx < -分裂(mod_tx seqnames (mod_tx))名称< -减少(相交,列表(名称(mod_tx)、名称(tx))) #得到相应的5 ' utr和3 ' utr注释fp < - fiveUTRsByTranscript tp (txdb) < - threeUTRsByTranscript (txdb) tx < - tx[名字]mod_tx < - mod_tx[名字]fp_m < -匹配(名称,名称(fp) fp_m < - fp_m [! is.na (fp_m)] tp_m < -匹配(名称,名称(tp)) tp_m < - tp_m [! is.na (tp_m)] fp < - fp fp_m tp < -tp (tp_m) #长度的记录,5 ' utr和3 ' utr tx_lengths < - sum(宽度(tx)) fp_lengths < -代表(0 l长度(tx))名称(fp_lengths) < -名称fp_lengths[名称(fp)] < - sum(宽度(fp) tp_lengths < -代表(0 l长度(tx))名称(tp_lengths) < -名称tp_lengths[名称(tp)] < - sum(宽度(tp)) #重新修改# cd开始在位置1 l和cd结束位置从< - 1000 l IRanges (fp_lengths + 1 l, tx_lengths - tp_lengths) <——IRanges (1000 l, l) mod_rescale < -重新调节(mod_tx,, from) # Construct result data.frame rel_pos <- data.frame(mod_type = unlist(mcols(mod_rescale,level="within")[,"mod_type"]), rel_pos = unlist(start(mod_rescale))) rel_pos <- rel_pos[rel_pos$rel_pos < 1500 & rel_pos$rel_pos > -500,] ## ----------------------------------------------------------------------------- library(ggplot2) ggplot(rel_pos[rel_pos$mod_type %in% c("m6A","m1A","Y"),], aes(x = rel_pos, colour = mod_type)) + geom_density() ## ----------------------------------------------------------------------------- sessionInfo()