```{r setup, echo=FALSE} library(LearnBioconductor) stopifnot(BiocInstaller::biocVersion() == "3.0")``` ```{r style, echo = FALSE, result = 'asis'} BiocStyle::markdown()“#形象化马丁·摩根。
2014年10月29日[Three methods](//www.andersvercelli.com/help/course-materials/2014/summerx/Visualization-slides.pdf) - 'base' graphics - _lattice_ - ' r CRANpkg("ggplot2") -一个整洁的_ggplot2_例子:[幻灯片19+](//www.andersvercelli.com/help/course-materials/2014/CSAMA2014/2_Tuesday/lectures/Visualization_in_Statistical_Genomics-Carey.pdf)摘自Vince Carey的演讲。以基因组为中心- ' r Biocpkg("Gviz") ' '可视化基因组区域- ' r Biocpkg("ggbio") ' '提供广泛的选项交互式可视化- ' r Biocpkg("rtracklayer") ' '可视化基因组范围和管理UCSC基因组浏览器会话。- ' r Biocpkg('epivizr') '交互式显示- ' r CRANpkg(' shiny ') ' [web](http://shiny.rstudio.com)交互式应用程序。报告- ' r Biocpkg("ReportingTools") '简单的报告模板和…-“r CRANpkg(“RColorBrewer”)”和[网站](http://colorbrewer2.org/):帮助选择明智的配色方案。——(意外艺术)(http://accidental-art.tumblr.com/archive)——(棒图)(https://github.com/EconometricsBySimulation/R-Graphics/blob/master/Stick-Figures/draw.stick.R) # # # # #实验室Gviz / ggbio工作通过[装饰图案部分2](//www.andersvercelli.com/packages/release/bioc/vignettes/Gviz/inst/doc/Gviz.pdf)的r Biocpkg (Gviz)的包,然后是[RNASeq lab](B02.1.1_RNASeqLab.html)中的“绘制基因组空间折叠变化”(plot fold changes in genomic space)。仔细阅读“r Biocpkg(‘ggbio’)”包的[插图](//www.andersvercelli.com/packages/release/bioc/vignettes/ggbio/inst/doc/ggbio.pdf)。运行以下_DESeq2_工作流到达一个top-table; coerce the result to a `data.frame`. ```{r ggplot-setup, eval=FALSE} library(DESeq2) library(airway) data(airway) se = airway dds <- DESeqDataSet(se, design = ~ cell + dex) dds$dex <- relevel(dds$dex, "untrt") dds <- DESeq(dds) res <- results(dds) resdf <- as.data.frame(res) ``` A 'volcano plot' shows the relationship between P-value and log fold change. Here's a basic volcano plot using base graphics; create a volcano plot using _ggplot2_ and / or _lattice_. ```{r volcano, eval=FALSE} plot(-log10(padj) ~ log2FoldChange, resdf) ```