R语言问题集锦

Ubuntu16.04-R3.4.2下安装clusterProf

2017-11-23  本文已影响723人  9d760c7ce737
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最近在学习聚类分析，看了Y叔的一系列帖子，觉得clusterProfiler就是传说中一包走天下的神包
在windows和mac都安装成功，这是背景。

在Ubuntu16.04，R3.4.2(2017-09-28)下运行一下命令，发生错误

source("https://bioconductor.org/biocLite.R")
biocLite('clusterProfiler')

** preparing package for lazy loading
Creating a new generic function for ‘append’ in package ‘BiocGenerics’
Creating a new generic function for ‘as.data.frame’ in package ‘BiocGenerics’
Creating a new generic function for ‘cbind’ in package ‘BiocGenerics’
Error : identical(as.call(parse(text = old_code)[[1L]]), body[[7L]][[3L]]) is not TRUE
Error in apply_hotfix73465(getGeneric("cbind")) :
hotfix failed for generic function cbind()
Error : unable to load R code in package ‘BiocGenerics’
ERROR: lazy loading failed for package ‘BiocGenerics’

如果仅仅运行这个代码

source("https://bioconductor.org/biocLite.R")
biocLite()

Error : unable to load R code in package ‘BiocGenerics’
ERROR: lazy loading failed for package ‘BiocGenerics’

追根溯源就是第一个‘BiocGenerics’没有安装成功
那我就来单独安装

source("https://bioconductor.org/biocLite.R")
biocLite('BiocGenerics')

报错信息如下：

** preparing package for lazy loading
Creating a new generic function for ‘append’ in package ‘BiocGenerics’
Creating a new generic function for ‘as.data.frame’ in package ‘BiocGenerics’
Creating a new generic function for ‘cbind’ in package ‘BiocGenerics’
Error : identical(as.call(parse(text = old_code)[[1L]]), body[[7L]][[3L]]) is not TRUE
Error in apply_hotfix73465(getGeneric("cbind")) :
hotfix failed for generic function cbind()
Error : unable to load R code in package ‘BiocGenerics’
ERROR: lazy loading failed for package ‘BiocGenerics’

实际上如果biocLite('BiocGenerics')装不上，那么内部缺少的依赖包不能通过biocLite('xxx')这种形式安装
在R语言中执行

 sessionInfo()

R version 3.4.2 (2017-09-28)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 16.04.3 LTS
Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.7.1
LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.7.1
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C LC_TIME=en_US.UTF-8
[4] LC_COLLATE=en_US.UTF-8 LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C LC_ADDRESS=C
[10] LC_TELEPHONE=C LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] parallel stats graphics grDevices utils datasets methods base
other attached packages:
[1] BiocInstaller_1.28.0 ggpubr_0.1.5 magrittr_1.5 ggplot2_2.2.1
[5] survival_2.41-3 dplyr_0.7.4 bindrcpp_0.2
loaded via a namespace (and not attached):
[1] Rcpp_0.12.13 compiler_3.4.2 plyr_1.8.4 bindr_0.1 tools_3.4.2
[6] tibble_1.3.4 gtable_0.2.0 nlme_3.1-131 lattice_0.20-35 pkgconfig_2.0.1
[11] rlang_0.1.2 Matrix_1.2-11 psych_1.7.8 yaml_2.1.14 knitr_1.17
[16] grid_3.4.2 glue_1.2.0 R6_2.2.2 foreign_0.8-69 scales_0.5.0
[21] splines_3.4.2 assertthat_0.2.0 mnormt_1.5-5 colorspace_1.3-2 lazyeval_0.2.1
[26] munsell_0.4.3

也看不出什么名堂
google发现有人在bioconduct社区提问了相同的问题：
https://support.bioconductor.org/p/101833/

给出来三种解决方法：
第一，说尝试打开一个新的R session可以解决问题

R --vanilla

照做后发现不能解决问题
有人在评论里面说

Glad that installing R 3.4.2 Patched solved the problem

但是这个版本我下载configure会报错(实际上是我不会编译R)就放弃了

我还看到有人说，

sudo apt-get install r-bioc-biocgenerics

这个命令可以解决问题
照做后显示我安装成功

(Reading database ... 185900 files and directories currently installed.)
Preparing to unpack .../r-bioc-biocgenerics_0.22.1-1ubuntu1_all.deb ...
Unpacking r-bioc-biocgenerics (0.22.1-1ubuntu1) ...
Setting up r-bioc-biocgenerics (0.22.1-1ubuntu1) ...

这时候我感到很高兴再来安装Y叔的包

source("https://bioconductor.org/biocLite.R")
biocLite('clusterProfiler')

又报错：

installing to /home/shipeng/opt/biosoft/R/bioconductor/S4Vectors/libs
** R
** inst
** preparing package for lazy loading
Error : package ‘BiocGenerics’ 0.22.1 was found, but >= 0.23.3 is required by ‘S4Vectors’
ERROR: lazy loading failed for package ‘S4Vectors’

提示我安装的版本不够高
好的，现在我的问题可能就是
安装版本高一点的R包，但是默认的biocLIte()是不行的
我查到可以通过github来安装,并且有两种方式
第一种方式需要知道包在github的名字，不是很方便

install.packages("devtools")
library(devtools)
install_github("xxx")

第二种方式方便一点

install.packages("githubinstall")

报错

ERROR: configuration failed for package ‘curl’

提示我缺少curl,那我就装一个

install.packages("curl")

报错

ERROR: configuration failed for package ‘curl’

还是没能解决,所以安装包的时候出现的问题，不能用R本身来解决！需要走其他的途径
网上说这个可以解决问题

sudo apt-get install libcurl4-openssl-dev

安装完事后我又试了一下

install.packages("githubinstall")

安装成功，那我就安装BiocGenerics试试

library(githubinstall)
githubinstall('BiocGenerics')

Select a number or, hit 0 to cancel.
1: Bioconductor/BiocGenerics S4 generic functions for Bioconductor
2: lshep/BiocGenerics alpha testing github
3: nturaga/BiocGenerics test
4: schifferl/BiocGenerics

试了第1个，第二个都失败
选择第三个后

** help
*** installing help indices
** building package indices
** testing if installed package can be loaded

成功!!!，我有开始安装Y叔的包

source("https://bioconductor.org/biocLite.R")
biocLite('clusterProfiler')

installing to /home/shipeng/opt/biosoft/R/bioconductor/S4Vectors/libs
** R
** inst
** preparing package for lazy loading
Error : package ‘BiocGenerics’ 0.23.0 was found, but >= 0.23.3 is required by ‘S4Vectors’

版本还是不够，这回真的没辙了
而使用biocLite()安装的报错信息我看不懂

Error : identical(as.call(parse(text = old_code)[[1L]]), body[[7L]][[3L]]) is not TRUE
Error in apply_hotfix73465(getGeneric("cbind")) :
hotfix failed for generic function cbind()

问了Y叔，给了我一个帖子无痛更新R包

rvcheck::update_all()

最后发现没有用

所以我来尝试一下帖子里说的安装R version 3.4.2 Patched
下载地址:
https://stat.ethz.ch/R/daily/

./configure

报错

error: --with-readline=yes (default) and headers/libs are not available

上网查找
https://stackoverflow.com/questions/20752307/error-in-install-previous-versions-of-r-on-ubuntu
这里提供解决方案

sudo apt-get install xorg-dev

https://cran.r-project.org/doc/manuals/R-admin.html#Essential-programs-and-libraries
这个文档给出详细的解释

Unless you do not want to view graphs on-screen (or use macOS) you need ‘X11’ installed, including its headers and client libraries. For recent Fedora/RedHat distributions it means (at least) RPMs ‘libX11’, ‘libX11-devel’, ‘libXt’ and ‘libXt-devel’. On Debian/Ubuntu we recommend the meta-package ‘xorg-dev’. If you really do not want these you will need to explicitly configure R without X11, using --with-x=no.

运行后提示：

R is now configured for x86_64-pc-linux-gnu
configure: WARNING: you cannot build info or HTML versions of the R manuals
configure: WARNING: you cannot build PDF versions of the R manuals
configure: WARNING: you cannot build PDF versions of vignettes and help pages

启动R

sudo R

R version 3.4.2 Patched (2017-11-05 r73673) -- "Short Summer"
Copyright (C) 2017 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

好了应该是按照成功了
尝试安装BiocGenerics

source("https://bioconductor.org/biocLite.R")
biocLite('BiocGenerics')

最终安装成功

** help
*** installing help indices
** building package indices
** testing if installed package can be loaded

可是我现在启动不了Rstudio

ERROR Unable to find libR.so in expected locations within R Home direc

把libR.so找到，复制指定目录下，最后发现rstudio成功，但是在rstudio所有R还是以前的版本
更改各种设置都不行，系统里面有两个R,删除掉其中一个
重新安装r

tar -xf R-patched_2017-11-05.tar.gz
sudo apt-get build-dep r-base-dev
./configure --enable-R-shlib=yes
make
make check
sudo make install

没有任何报错！！！
https://bookdown.org/yihui/r-ninja/setup.html#r
谢益辉说的这个无敌命令一次性解决依赖问题

sudo apt-get build-dep r-base-dev

在终端启动R

source("https://bioconductor.org/biocLite.R")
options(BioC_mirror="http://mirrors.ustc.edu.cn/bioc/")
biocLite('clusterProfiler')

报错
说没有装上igraph

apt-get install -y r-cran-igraph

报错

E: Could not open lock file /var/lib/dpkg/lock - open (13: Permission denied)
E: Unable to lock the administration directory (/var/lib/dpkg/), are you root?

加上root权限：

sudo apt-get install -y r-cran-igraph

安装完了之后，在r里面无法library

ibrary(igragh)

使用

install.packages("igraph")

安装成功
再来安装Y叔的包
DOSE包安装失败
安装DOSE包

devtools::install_github("GuangchuangYu/DOSE")

报错

Error in dyn.load(file, DLLpath = DLLpath, ...) :
unable to load shared object '/home/shipeng/opt/biosoft/R/bioconductor/stringi/libs/stringi.so':
libicui18n.so.57: cannot open shared object file: No such file or directory

安装

install.packages("stringi")

安装

biocLite('DOSE')

成功

biocLite('clusterProfiler')

成功！！！
测试数据：

biocLite("ggridges")
require(clusterProfiler)
data(geneList)
x <- gseKEGG(geneList)
ridgeplot(x,showCategory = 60)

出图如下：这图出的不容易！！！！！


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