# # = FALSE,消息,警告= FALSE,包括= FALSE ------------------------------ 图书馆(wheatmap)图书馆(rmarkdown.html_vignette (dplyr)选项。check_title = FALSE) # #——nh1消息= FALSE ------------------------------------------------------- 图书馆sesameDataCache(芝麻) () ## ---- nh3、消息= FALSE eval = FALSE ------------------------------------------- # tmp = tempdir () # sesameAnno_download(“测试/ GSM4411982_Grn.idat.gz dest_dir = tmp) # sesameAnno_download(“测试/ GSM4411982_Red.idat.gz dest_dir = tmp) #贝塔= openSesame (sprintf(“% s /测试/ GSM4411982 tmp),准备= " SHCDPM ") ## ---- 铵根离子,eval = FALSE ---------------------------------------------------------- # ## 相当于上述openSesame调用#贝塔= getBetas (matchDesign(称他(dyeBiasNL (inferInfiniumIChannel (# prefixMaskButC (inferSpecies (readIDATpair (# sprintf(“% s /测试/ GSM4411982 tmp ))))))))) ## ---- nh13、消息= FALSE eval = TRUE ------------------------------------------- 自卫队= sesameDataGet (Mammal40.1.SigDF) #一个例子SigDF inferSpecies (sdf,返回。物种= TRUE) # #——nh14消息= FALSE ------------------------------------------------------ ## 显示候选物种得分最高的头(排序(inferSpecies (sdf,回报。auc = TRUE),减少= TRUE )) ## ---- nh15 eval = FALSE --------------------------------------------------------- # sdf_mouse < updateSigDF (sdf,物种= " mus_musculus ") ## ---- 氨基,消息= FALSE, eval = FALSE ------------------------------------------- # tmp = tempdir () # sesameAnno_download(“测试/ 204637490002 _r05c01_grn。# sesameAnno_download("Test/204637490002_R05C01_Red. dat"， dest_dir=tmp) #idat”,dest_dir = tmp) #贝塔= openSesame (sprintf(“% s /测试/ 204637490002 _r05c01 tmp),准备= " TQCDPB ") ## ---- nh9、消息= FALSE ------------------------------------------------------- 自卫队= sesameDataGet (MM285.1.SigDF) #一个示例数据集inferStrain (sdf,返回。strain = TRUE) #返回string形式的应变sdf_after = inferStrain(sdf) #更新掩码和col by应变推理sum(sdf$mask) #前应变推理sum(sdf_after$mask) #后应变推理## ----nh10, fig.width=6, fig.height=4, message=FALSE--------------------------- library(ggplot2) p = inferStrain(sdf，返回。概率= TRUE) df = data.frame(strain=names(p)， probs=p) ggplot(data = df, aes(x = strain, y = probs)) + geom_bar(stat =" identity"， color="gray") + ggtitle(" strain probability ") + ylab(" probability ") + xlab("") + scale_x_discrete(position =" top") + theme(轴.text。X = element_text(角度= 90,vjust=0.5, hjust=0)，图例。位置= "没有 ") ## ---- nh7、消息= FALSE ------------------------------------------------------- 自卫队= sesameDataGet(“MM285.1.SigDF”)和(。na(openSesame(sdf, prep="TQCDPB")))na (openSesame (sdf,准备= " TQCD0PB "))) ## ----------------------------------------------------------------------------- sessionInfo ()