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增强火山图，要不要试一下？

發(fā)布時(shí)間：2025/3/15 编程问答 49 豆豆

生活随笔收集整理的這篇文章主要介紹了增强火山图，要不要试一下？小編覺得挺不錯(cuò)的,現(xiàn)在分享給大家,幫大家做個(gè)參考.

包作者：Kevin Blighe

撰文：協(xié)和醫(yī)學(xué)院苑曉梅

編輯：生信寶典?

前言

最近道聽途說EnhancedVolcano繪制火山圖的方便性，所以本人就根據(jù)其說明文檔進(jìn)行操作。但在操作過程中發(fā)現(xiàn)，其shape功能并沒有在help文檔中找到，經(jīng)過搜索在github上看到了以下的答復(fù) 。。。（說明整個(gè)文檔功能并沒有完全開發(fā)，需進(jìn)行選擇）

1 Introduction

火山圖是可視化差異表達(dá)分析結(jié)果的有效方法。這次更新的EnhancedVolcano目的就是兩個(gè)（1）使轉(zhuǎn)錄本基因名稱的顯示更加的合理化，避免出現(xiàn)相互重疊的現(xiàn)象；（2）允許用戶通過顏色，形狀和陰影參數(shù)配置在同一繪圖空間中識(shí)別多達(dá)3種不同類型的屬性。

2 Installation

2.1 1. 下載安裝包

# if (!requireNamespace('BiocManager', quietly = TRUE)) # install.packages('BiocManager') # BiocManager::install('EnhancedVolcano') if (!requireNamespace('devtools', quietly = TRUE))install.packages('devtools') devtools::install_github('kevinblighe/EnhancedVolcano')

2.2 2. 加載R包

library(EnhancedVolcano)

3 開始

作者使用該流程： RNA-seq workflow: gene-level exploratory analysis and differential expression。具體來說，我們將加載airway數(shù)據(jù)，其中不同的氣道平滑肌細(xì)胞用地塞米松治療。

library(airway) library(magrittr)data('airway') # %<>%復(fù)合賦值操作符，功能與 %>% 基本是一樣的，但多了一項(xiàng)額外的操作，就是把結(jié)果寫到左側(cè)對(duì)象。 # 對(duì)dex列進(jìn)行relevel，再把revel后的結(jié)果賦值到airway$dex。 airway$dex %<>% relevel('untrt')

使用DESeq2進(jìn)行差異表達(dá)，以創(chuàng)建兩組結(jié)果(DESeq2差異基因分析和批次效應(yīng)移除)：

library('DESeq2')dds <- DESeqDataSet(airway, design = ~ cell + dex)dds <- DESeq(dds, betaPrior=FALSE)# compare trt & untrtres1 <- results(dds,contrast = c('dex','trt','untrt'))# shrink log2 fold changeres1 <- lfcShrink(dds,contrast = c('dex','trt','untrt'), res=res1)# compare different cellsres2 <- results(dds,contrast = c('cell', 'N061011', 'N61311'))res2 <- lfcShrink(dds,contrast = c('cell', 'N061011', 'N61311'), res=res2)

查看下數(shù)據(jù)結(jié)構(gòu)

head res1log2 fold change (MAP): dex trt vs untrt Wald test p-value: dex trt vs untrt DataFrame with 6 rows and 6 columnsbaseMean log2FoldChange lfcSE<numeric> <numeric> <numeric> ENSG00000000003 708.602169691234 -0.374152710396614 0.0988428916720785 ENSG00000000005 0 NA NA ENSG00000000419 520.297900552084 0.202062036081026 0.109739490807055 ENSG00000000457 237.163036796015 0.0361672062398394 0.138337785736641 ENSG00000000460 57.9326331250967 -0.0844566831590659 0.249890471495246 ENSG00000000938 0.318098378392895 -0.0841390331826692 0.151334283397515stat pvalue padj<numeric> <numeric> <numeric> ENSG00000000003 -3.7877506903658 0.000152017272634539 0.00128363812227422 ENSG00000000005 NA NA NA ENSG00000000419 1.84294384315416 0.0653372100766985 0.19654584069126 ENSG00000000457 0.264356843264039 0.791504963002101 0.911458000845921 ENSG00000000460 -0.307052600205469 0.758803335537917 0.895034449952733 ENSG00000000938 -0.39379516719652 0.693732272741941 NA

3.1 繪制最基本的火山圖

對(duì)于最基本的火山圖，只需要一個(gè)數(shù)據(jù)框或測(cè)試結(jié)果矩陣，包含轉(zhuǎn)錄本名稱，log2FC以及adjusted或unajusted的P值。 log2FC的默認(rèn)cut-off值是 > | 2 |; P值的默認(rèn)cut-off值為10e-6。

EnhancedVolcano(res1,# 基因名字lab = rownames(res1),x = 'log2FoldChange',y = 'pvalue',xlim = c(-5, 8))

圖例：NS-非顯著基因；Log2 FC倍數(shù)大于閾值的基因；P 統(tǒng)計(jì)顯著的基因；P & Log2 FC 差異基因

4 高級(jí)功能

默認(rèn)情況下，EnhancedVolcano將僅嘗試標(biāo)記設(shè)置的閾值篩選出的差異基因，即p Cutoff和FC cutoff。此外，它只會(huì)標(biāo)記可以合理地適合繪圖空間的基因。用戶可以選擇性地提供他/她希望在圖中標(biāo)記的轉(zhuǎn)錄本名稱的矢量（as selectLab）。

在這個(gè)例子中，還修改了點(diǎn)和標(biāo)簽大小，幫助改善清晰度，保障更多的轉(zhuǎn)錄本進(jìn)入差異分析中。

4.2 調(diào)整點(diǎn)的顏色和透明度

默認(rèn)配色方案可能不是每個(gè)人都喜歡。在這里，只有通過log2FC和P值篩選的差異轉(zhuǎn)錄本都是紅色的，其他一切都是黑色的。還調(diào)整’alpha’的值，它控制繪制點(diǎn)的透明度：1 = 100％不透明; 0 = 100％透明。

EnhancedVolcano(res2,lab = rownames(res2),x = 'log2FoldChange',y = 'pvalue',xlim = c(-8, 8),title = 'N061011 versus N61311',pCutoff = 10e-16,FCcutoff = 1.5,transcriptPointSize = 1.5,transcriptLabSize = 3.0,# Colour shading for plotted points, corresponding to < abs(FCcutoff) && > pCutoff, # > abs(FCcutoff), < pCutoff, > abs(FCcutoff) && < pCutoff. # 無顯著，倍數(shù)大（左下、右下），P小 (中上), 顯著差異# > DEFAULT = c("grey30", "forestgreen", "royalblue", "red2").col=c('black', 'black', 'black', 'red3'),colAlpha = 1)

4.3 調(diào)整繪制點(diǎn)的形狀

它可以幫助將不同的點(diǎn)繪制成不同的形狀。默認(rèn)形狀是圓形。用戶可以通過shape參數(shù)指定形狀，該參數(shù)接受單個(gè)或四個(gè)可能的值：如果有四個(gè)值，則這些值將映射到也由顏色指定的標(biāo)準(zhǔn)名稱; 如果是單個(gè)值，則所有點(diǎn)都用此值繪制。

For more information on shape encoding search online at ggplot2 Quick Reference: shape

調(diào)整畫圖點(diǎn)的形狀

4.4 調(diào)整cut-off線并添加額外的閾值線

cut-off線可以通過以下參數(shù)進(jìn)行調(diào)整。 “cutoffLineType”以下參數(shù)進(jìn)行修改：“blank”, “solid”, “dashed”, “dotted”, “dotdash”, “l(fā)ongdash”, ?“twodash”；cutoff線的顏色和粗細(xì)可以通過 ‘cutoffLineCol’ 和 ‘cutoffLineWidth’進(jìn)行修改，如果不需要該cut-off線，可以設(shè)置“cutoffLineType=“blank” or cutoffLineWidth=0.”

也可以通過參數(shù)‘hline’ and ‘vline’ ?顯示其他的cut-off線；

EnhancedVolcano(res2,lab = rownames(res2),x = 'log2FoldChange',y = 'pvalue',xlim = c(-6, 6),title = 'N061011 versus N61311',pCutoff = 10e-12,FCcutoff = 1.5,transcriptPointSize = 1.5,transcriptLabSize = 3.0,colAlpha = 1,# 取消cutoff線cutoffLineType = 'blank',cutoffLineCol = 'black',cutoffLineWidth = 0.8,hline = c(10e-12, 10e-36, 10e-60, 10e-84),hlineCol = c('grey0', 'grey25','grey50','grey75'),hlineType = 'longdash',hlineWidth = 0.8,gridlines.major = FALSE,gridlines.minor = FALSE)

4.5 調(diào)整圖例位置，大小和文本

EnhancedVolcano(res2,lab = rownames(res2),x = 'log2FoldChange',y = 'pvalue',xlim = c(-6, 6),pCutoff = 10e-12,FCcutoff = 1.5,cutoffLineType = 'twodash',cutoffLineWidth = 0.8,transcriptPointSize = 3.0,transcriptLabSize = 4.0,colAlpha = 1,legend=c('NS','Log (base 2) fold-change','P value', 'P value & Log (base 2) fold-change'),legendPosition = 'right',legendLabSize = 16,legendIconSize = 5.0)

4.6 繪制調(diào)整后的p值

作者通過 bquote 函數(shù)修改軸標(biāo)題

EnhancedVolcano(res2,lab = rownames(res2),x = 'log2FoldChange',y = 'padj',xlim=c(-6,6),xlab = bquote(~Log[2]~ 'fold change'),ylab = bquote(~-Log[10]~adjusted~italic(P)),pCutoff = 0.0001,FCcutoff = 1.0,transcriptLabSize = 4.0,colAlpha = 1,legend=c('NS','Log2 FC','Adjusted p-value','Adjusted p-value & Log2 FC'),legendPosition = 'bottom',legendLabSize = 10,legendIconSize = 3.0)

4.7 通過添加連接線來添加更多標(biāo)簽

為了標(biāo)記更多點(diǎn)，可以通過短線連接點(diǎn)和標(biāo)簽, 這些連接線的寬度和顏色也可以分別用widthConnectors和colConnectors進(jìn)行修改；

EnhancedVolcano(res2,lab = rownames(res2),x = 'log2FoldChange',y = 'pvalue',xlim = c(-6,6),xlab = bquote(~Log[2]~ 'fold change'),pCutoff = 10e-14,FCcutoff = 2.0,transcriptPointSize = 3.0,transcriptLabSize = 4.0,colAlpha = 1,legend=c('NS','Log (base 2) fold-change','P value', 'P value & Log (base 2) fold-change'),legendPosition = 'right',legendLabSize = 12,legendIconSize = 4.0,drawConnectors = TRUE,widthConnectors = 0.2,colConnectors = 'grey30')

4.8 僅標(biāo)記關(guān)鍵轉(zhuǎn)錄本

在許多情況下，人們可能只希望標(biāo)記他們感興趣的關(guān)鍵轉(zhuǎn)錄本。因此，可以通過selectLab參數(shù)提要標(biāo)記的轉(zhuǎn)錄本的名字。當(dāng)然，只有通過差異基因閾值篩選的名字才會(huì)被標(biāo)記。

EnhancedVolcano(res2,lab = rownames(res2),x = 'log2FoldChange',y = 'pvalue',## 標(biāo)記目標(biāo)基因selectLab = c('ENSG00000106565','ENSG00000187758'),xlim = c(-6,7),xlab = bquote(~Log[2]~ 'fold change'),pCutoff = 10e-14,FCcutoff = 2.0,transcriptPointSize = 3.0,transcriptLabSize = 5.0,shape = c(4, 35, 17, 18),colAlpha = 1,legend=c('NS','Log (base 2) fold-change','P value','P value & Log (base 2) fold-change'),legendPosition = 'right',legendLabSize = 14,legendIconSize = 5.0)

4.9 給標(biāo)簽加框

EnhancedVolcano(res2,lab = rownames(res2),x = 'log2FoldChange',y = 'pvalue',selectLab = c('ENSG00000106565','ENSG00000187758','ENSG00000230795', 'ENSG00000164530','ENSG00000143153'),xlim = c(-5.5,8),xlab = bquote(~Log[2]~ 'fold change'),pCutoff = 10e-14,FCcutoff = 2.0,transcriptPointSize = 3.0,transcriptLabSize = 5.0,transcriptLabCol = 'black',transcriptLabFace = 'bold',# 加框boxedlabels = TRUE,colAlpha = 4/5,legend=c('NS','Log (base 2) fold-change','P value','P value & Log (base 2) fold-change'),legendPosition = 'right',legendLabSize = 14,legendIconSize = 4.0,drawConnectors = TRUE,widthConnectors = 1.0,colConnectors = 'black')

4.10 使用自定義值著色方案

在這個(gè)例子，作者希望將log2FC> 2.5的所有轉(zhuǎn)錄本標(biāo)記為“high”，將log2FC <-2.5的轉(zhuǎn)錄本標(biāo)記為“l(fā)ow”。

# create custom key-value pairs for 'high', 'low', 'mid' expression by fold-change # 通過named vector生成自定義顏色# set the base colour as 'black'keyvals <- rep('black', nrow(res2))# set the base name/label as 'Mid'names(keyvals) <- rep('Mid', nrow(res2))# modify keyvals for transcripts with fold change > 2.5keyvals[which(res2$log2FoldChange > 2.5)] <- 'gold'names(keyvals)[which(res2$log2FoldChange > 2.5)] <- 'high'# modify keyvals for transcripts with fold change < -2.5keyvals[which(res2$log2FoldChange < -2.5)] <- 'royalblue'names(keyvals)[which(res2$log2FoldChange < -2.5)] <- 'low'unique(names(keyvals))## [1] "Mid" "low" "high" unique(keyvals)## [1] "black" "royalblue" "gold" keyvals[1:20]## Mid Mid Mid Mid Mid Mid Mid Mid Mid ## "black" "black" "black" "black" "black" "black" "black" "black" "black" ## Mid Mid Mid Mid Mid Mid Mid Mid Mid ## "black" "black" "black" "black" "black" "black" "black" "black" "black" ## Mid Mid ## "black" "black" p1 <- EnhancedVolcano(res2,lab = rownames(res2),x = 'log2FoldChange',y = 'pvalue',selectLab = rownames(res2)[which(names(keyvals) %in% c('high', 'low'))],xlim = c(-6.5,6.5),xlab = bquote(~Log[2]~ 'fold change'),title = 'Custom colour over-ride',pCutoff = 10e-14,FCcutoff = 1.0,transcriptPointSize = 3.5,transcriptLabSize = 4.5,shape = c(6, 4, 2, 11),# 自定義顏色colCustom = keyvals,colAlpha = 1,legendPosition = 'top',legendLabSize = 15,legendIconSize = 5.0,drawConnectors = TRUE,widthConnectors = 0.5,colConnectors = 'grey50',gridlines.major = TRUE,gridlines.minor = FALSE,border = 'partial',borderWidth = 1.5,borderColour = 'black')p2 <- EnhancedVolcano(res2,lab = rownames(res2),x = 'log2FoldChange',y = 'pvalue',selectLab = rownames(res2)[which(names(keyvals) %in% c('high', 'low'))],xlim = c(-6.5,6.5),xlab = bquote(~Log[2]~ 'fold change'),title = 'No custom colour over-ride',pCutoff = 10e-14,FCcutoff = 1.0,transcriptPointSize = 3.5,transcriptLabSize = 4.5,colCustom = NULL,colAlpha = 1,legendPosition = 'top',legendLabSize = 15,legendIconSize = 5.0,drawConnectors = FALSE,widthConnectors = 0.5,colConnectors = 'grey50',gridlines.major = TRUE,gridlines.minor = FALSE,border = 'full',borderWidth = 1.0,borderColour = 'black')library(gridExtra)library(grid)grid.arrange(p1, p2,ncol=2,top = textGrob('EnhancedVolcano',just = c('center'),gp = gpar(fontsize = 32)))grid.rect(gp=gpar(fill=NA))

4.11 使用自定義value對(duì)覆蓋顏色和/或形狀進(jìn)行修改

# define different cell-types that will be shadedcelltype1 <- c('ENSG00000106565', 'ENSG00000002933','ENSG00000165246', 'ENSG00000224114')celltype2 <- c('ENSG00000230795', 'ENSG00000164530','ENSG00000143153', 'ENSG00000169851','ENSG00000231924', 'ENSG00000145681')# create custom key-value pairs for different cell-types# set the base shape as '3'keyvals.shape <- rep(3, nrow(res2))# set the base name/label as 'PBC'names(keyvals.shape) <- rep('PBC', nrow(res2))# modify the keyvals for cell-type 1keyvals.shape[which(rownames(res2) %in% celltype1)] <- 17names(keyvals.shape)[which(rownames(res2) %in% celltype1)] <- 'Cell-type 1'# modify the keyvals for cell-type 2keyvals.shape[which(rownames(res2) %in% celltype2)] <- 64names(keyvals.shape)[which(rownames(res2) %in% celltype2)] <- 'Cell-type 2'unique(names(keyvals.shape))## [1] "PBC" "Cell-type 1" "Cell-type 2" unique(keyvals.shape)## [1] 3 17 64 keyvals.shape[1:20]## PBC PBC PBC PBC PBC PBC PBC PBC PBC PBC PBC PBC PBC PBC PBC PBC PBC PBC ## 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 ## PBC PBC ## 3 3 p1 <- EnhancedVolcano(res2,lab = rownames(res2),x = 'log2FoldChange',y = 'pvalue',selectLab = rownames(res2)[which(names(keyvals) %in% c('high', 'low'))],xlim = c(-6.5,6.5),xlab = bquote(~Log[2]~ 'fold change'),title = 'Custom shape over-ride',pCutoff = 10e-14,FCcutoff = 1.0,transcriptPointSize = 3.5,transcriptLabSize = 4.5,shapeCustom = keyvals.shape,colCustom = NULL,colAlpha = 1,legendLabSize = 15,legendPosition = 'left',legendIconSize = 5.0,drawConnectors = TRUE,widthConnectors = 0.5,colConnectors = 'grey50',gridlines.major = TRUE,gridlines.minor = FALSE,border = 'partial',borderWidth = 1.5,borderColour = 'black')# create custom key-value pairs for 'high', 'low', 'mid' expression by fold-change# set the base colour as 'black'keyvals.colour <- rep('black', nrow(res2))# set the base name/label as 'Mid'names(keyvals.colour) <- rep('Mid', nrow(res2))# modify keyvals for transcripts with fold change > 2.5keyvals.colour[which(res2$log2FoldChange > 2.5)] <- 'gold'names(keyvals.colour)[which(res2$log2FoldChange > 2.5)] <- 'high'# modify keyvals for transcripts with fold change < -2.5keyvals.colour[which(res2$log2FoldChange < -2.5)] <- 'royalblue'names(keyvals.colour)[which(res2$log2FoldChange < -2.5)] <- 'low'unique(names(keyvals.colour))## [1] "Mid" "low" "high" unique(keyvals.colour)## [1] "black" "royalblue" "gold"p2 <- EnhancedVolcano(res2,lab = rownames(res2),x = 'log2FoldChange',y = 'pvalue',selectLab = rownames(res2)[which(names(keyvals) %in% c('High', 'Low'))],xlim = c(-6.5,6.5),xlab = bquote(~Log[2]~ 'fold change'),title = 'Custom shape & colour over-ride',pCutoff = 10e-14,FCcutoff = 1.0,transcriptPointSize = 5.5,transcriptLabSize = 0.0,shapeCustom = keyvals.shape,colCustom = keyvals.colour,colAlpha = 1,legendPosition = 'top',legendLabSize = 15,legendIconSize = 5.0,drawConnectors = TRUE,widthConnectors = 0.5,colConnectors = 'grey50',gridlines.major = TRUE,gridlines.minor = FALSE,border = 'full',borderWidth = 1.0,borderColour = 'black')library(gridExtra)library(grid)grid.arrange(p1, p2,ncol=2,top = textGrob('EnhancedVolcano',just = c('center'),gp = gpar(fontsize = 32)))grid.rect(gp=gpar(fill=NA))

4.12 Shade 指定的轉(zhuǎn)錄本

此功能最適用于僅顯示1或2個(gè)關(guān)鍵轉(zhuǎn)錄本。用戶可以使用’shapeCustom’參數(shù)來更識(shí)別不同類型的轉(zhuǎn)錄本。

# define different cell-types that will be shadedcelltype1 <- c('ENSG00000106565', 'ENSG00000002933')celltype2 <- c('ENSG00000230795', 'ENSG00000164530')p1 <- EnhancedVolcano(res2,lab = rownames(res2),x = 'log2FoldChange',y = 'pvalue',selectLab = celltype1,xlim = c(-6.5,6.5),xlab = bquote(~Log[2]~ 'fold change'),title = 'Shading cell-type 1',pCutoff = 10e-14,FCcutoff = 1.0,transcriptPointSize = 8.0,transcriptLabSize = 5.0,transcriptLabCol = 'purple',transcriptLabFace = 'bold',boxedlabels = TRUE,shape = 42,# 自定義顏色colCustom = keyvals,colAlpha = 1,legendPosition = 'top',legendLabSize = 15,legendIconSize = 5.0,# 自定義標(biāo)簽的背景shade = celltype1,shadeLabel = 'Cell-type I',shadeAlpha = 1/2,shadeFill = 'purple',shadeSize = 1,shadeBins = 5,drawConnectors = TRUE,widthConnectors = 1.0,colConnectors = 'grey30',gridlines.major = TRUE,gridlines.minor = FALSE,border = 'partial',borderWidth = 1.5,borderColour = 'black')p2 <- EnhancedVolcano(res2,lab = rownames(res2),x = 'log2FoldChange',y = 'pvalue',selectLab = celltype2,xlim = c(-6.5,6.5),xlab = bquote(~Log[2]~ 'fold change'),title = 'Shading cell-type 2',pCutoff = 10e-14,FCcutoff = 1.0,transcriptLabSize = 5.0,transcriptLabCol = 'forestgreen',transcriptLabFace = 'bold',# 自定義形狀shapeCustom = keyvals.shape,colCustom = keyvals.colour,colAlpha = 1,legendPosition = 'top',transcriptPointSize = 4.0,legendLabSize = 15,legendIconSize = 5.0,shade = celltype2,shadeLabel = 'Cell-type II',shadeAlpha = 1/2,shadeFill = 'forestgreen',shadeSize = 1,shadeBins = 5,drawConnectors = TRUE,widthConnectors = 1.0,colConnectors = 'grey30',gridlines.major = TRUE,gridlines.minor = FALSE,border = 'full',borderWidth = 1.0,borderColour = 'black')library(gridExtra)library(grid)grid.arrange(p1, p2,ncol=2,top = textGrob('EnhancedVolcano',just = c('center'),gp = gpar(fontsize = 32)))grid.rect(gp=gpar(fill=NA))

5 Session info

sessionInfo()## R version 3.6.0 (2019-04-26) ## Platform: x86_64-pc-linux-gnu (64-bit) ## Running under: Ubuntu 18.04.2 LTS ## ## Matrix products: default ## BLAS: /home/biocbuild/bbs-3.10-bioc/R/lib/libRblas.so ## LAPACK: /home/biocbuild/bbs-3.10-bioc/R/lib/libRlapack.so ## ## locale: ## [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C ## [3] LC_TIME=en_US.UTF-8 LC_COLLATE=C ## [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8 ## [7] LC_PAPER=en_US.UTF-8 LC_NAME=C ## [9] LC_ADDRESS=C LC_TELEPHONE=C ## [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C ## ## attached base packages: ## [1] grid parallel stats4 stats graphics grDevices utils ## [8] datasets methods base ## ## other attached packages: ## [1] gridExtra_2.3 DESeq2_1.25.0 ## [3] magrittr_1.5 airway_1.5.0 ## [5] SummarizedExperiment_1.15.1 DelayedArray_0.11.0 ## [7] BiocParallel_1.19.0 matrixStats_0.54.0 ## [9] Biobase_2.45.0 GenomicRanges_1.37.8 ## [11] GenomeInfoDb_1.21.1 IRanges_2.19.6 ## [13] S4Vectors_0.23.6 BiocGenerics_0.31.2 ## [15] EnhancedVolcano_1.3.1 ggrepel_0.8.1 ## [17] ggplot2_3.1.1 knitr_1.23 ## ## loaded via a namespace (and not attached): ## [1] bit64_0.9-7 splines_3.6.0 Formula_1.2-3 ## [4] assertthat_0.2.1 highr_0.8 latticeExtra_0.6-28 ## [7] blob_1.1.1 GenomeInfoDbData_1.2.1 yaml_2.2.0 ## [10] RSQLite_2.1.1 pillar_1.4.1 backports_1.1.4 ## [13] lattice_0.20-38 glue_1.3.1 digest_0.6.19 ## [16] RColorBrewer_1.1-2 XVector_0.25.0 checkmate_1.9.3 ## [19] colorspace_1.4-1 htmltools_0.3.6 Matrix_1.2-17 ## [22] plyr_1.8.4 XML_3.98-1.19 pkgconfig_2.0.2 ## [25] genefilter_1.67.1 zlibbioc_1.31.0 purrr_0.3.2 ## [28] xtable_1.8-4 scales_1.0.0 tibble_2.1.2 ## [31] htmlTable_1.13.1 annotate_1.63.0 withr_2.1.2 ## [34] nnet_7.3-12 lazyeval_0.2.2 survival_2.44-1.1 ## [37] crayon_1.3.4 memoise_1.1.0 evaluate_0.14 ## [40] MASS_7.3-51.4 foreign_0.8-71 tools_3.6.0 ## [43] data.table_1.12.2 stringr_1.4.0 locfit_1.5-9.1 ## [46] munsell_0.5.0 cluster_2.0.9 AnnotationDbi_1.47.0 ## [49] compiler_3.6.0 rlang_0.3.4 RCurl_1.95-4.12 ## [52] rstudioapi_0.10 htmlwidgets_1.3 labeling_0.3 ## [55] bitops_1.0-6 base64enc_0.1-3 rmarkdown_1.13 ## [58] gtable_0.3.0 DBI_1.0.0 R6_2.4.0 ## [61] dplyr_0.8.1 bit_1.1-14 Hmisc_4.2-0 ## [64] stringi_1.4.3 Rcpp_1.0.1 geneplotter_1.63.0 ## [67] rpart_4.1-15 acepack_1.4.1 tidyselect_0.2.5 ## [70] xfun_0.7

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