## ---- echo = TRUE, results = 'hide', message = FALSE, warning = FALSE--------- library(SBGNview) library(SummarizedExperiment) data("IFNg", "pathways.info”）count.data < - assays（ifng）$ counts head（count.data）wt.cols < - who（ifng $ group ==“ wt”））## ---- echo = true，结果='hide'，messages = false，parning = false ------- eNSEMBL.Pathway <-sbgn.gsets（id.type =“ eNsembl”，temp =“mmu", mol.type = "gene", output.pathway.name = TRUE ) head(ensembl.pathway[[2]]) ## ---- echo = TRUE, results = 'hide', message = FALSE,警告= false -------- if（！sireseenamespace（“ gage”，emile = true））{biocmanager :: install（“ gage”，update = false）} library（gage）degs degs <-gage（exprs = count.data，gsets = ensembl.pathway，ref = wt.cols，samp = ko.cols，compare =“配对”＃“ as.group”）head（degs $ greem）[，3：5]deg $ siss）[，3：5] down.Pathways <-Row.names（DEGS $ LISE）[1:10] head（down.pathways）## ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------消息= false，警告= false------------------ emembl.kovswt <-count.data [，ko.cols] -count.data [，wt.cols] head（ensembl.kovswt）＃alternesty，我们也可以计算平均折叠更改Gene，对应于上面的GAGE分析，并具有compare =“ as.group”平均值。应用（count.data [，ko.cols]，1，“均值”）头（均值。因此，折叠是它们的差异。Ensembl.kovswt.m < - sean.ko -ko-nee.wt ## ---- echo = true，结果='hide'，message = false，pardning = false = false-----------------------------------------------------------------------------途径收集，这可能需要几秒钟。 data(sbgn.xmls) down.pathways <- sapply(strsplit(down.pathways,"::"), "[", 1) head(down.pathways) sbgnview.obj <- SBGNview( gene.data = ensembl.koVsWt, gene.id.type = "ENSEMBL", input.sbgn = down.pathways[1:2],#can be more than 2 pathways output.file = "ifn.sbgnview.less", show.pathway.name = TRUE, max.gene.value = 2, min.gene.value = -2, mid.gene.value = 0, node.sum = "mean", output.format = c("png"), font.size = 2.3, org = "mmu", text.length.factor.complex = 3, if.scale.compartment.font.size = TRUE, node.width.adjust.factor.compartment = 0.04 ) sbgnview.obj ## ----ifng, echo = FALSE,fig.cap="\\label{fig:ifng}SBGNview graph of the most down-regulated pathways in IFNg KO experiment"---- library(knitr) include_graphics("ifn.sbgnview.less_R-HSA-877300_Interferon gamma signaling.svg") ## ----ifna, echo = FALSE,fig.cap="\\label{fig:ifna}SBGNview graph of the second most down-regulated pathways in IFNg KO experiment"---- library(knitr) include_graphics("ifn.sbgnview.less_R-HSA-909733_Interferon alpha_beta signaling.svg") ## ---- echo = TRUE, results = 'hide', message = FALSE, warning = FALSE--------- data("cancer.ds") sbgnview.obj <- SBGNview( gene.data = cancer.ds, gene.id.type = "ENTREZID", input.sbgn = "R-HSA-877300", output.file = "demo.SummarizedExperiment", show.pathway.name = TRUE, max.gene.value = 1, min.gene.value = -1, mid.gene.value = 0, node.sum = "mean", output.format = c("png"), font.size = 2.3, org = "hsa", text.length.factor.complex = 3, if.scale.compartment.font.size = TRUE, node.width.adjust.factor.compartment = 0.04 ) sbgnview.obj ## ----cancerds, echo = FALSE,fig.cap="\\label{fig:cancerds}SBGNview of a cancer dataset gse16873"---- include_graphics("demo.SummarizedExperiment_R-HSA-877300_Interferon gamma signaling.svg") ## ----------------------------------------------------------------------------- sessionInfo()