# 导入包 library(rgl) Sys.setenv(LANGUAGE = "en") #显示英文报错信息 options(stringsAsFactors = FALSE) #禁止chr转成factor 导入表达量数据 # 读取表达量数据 df <- read.csv("PCA_inputdata.csv", header = T, row.names = 1) df[1:5,1:5] > df[1:5,1:5] sample001 sample002 sample003...
Sys.setenv(LANGUAGE = "en") 7 R包如何使用-获取帮助 7.1 快速查看函数帮助文档 “?”+函数名 ?sd sd(x,na.rm = FALSE) #若存在缺失值则应写sd(x,na.rm=TRUE) 7.2 找R包介绍页面 limma:Linear Models for Microarray Data browseVignettes("limma") 7.3 Vignettes browseVignettes("limma") #同上 7...
r语言nlme包使用教程 r语言limma包教程 1. 制作三个矩阵2. 建模前归一化3. 建模及结果4.检查 #加载包和数据 if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager") if (!require("edgeR", quietly = TRUE)) BiocManager::install("edgeR") o r语言nlme包使用教程 归...
5.是否更新 代码语言:javascript 复制 >BiocManager::install("limma")'getOption("repos")'replaces Bioconductor standard repositories,see 'help("repositories",package="BiocManager")'fordetails.Replacement repositories:CRAN:https://mirrors.tuna.tsinghua.edu.cn/CRAN/Bioconductor version3.18(BiocManager1.30.23)...
r语言nlme包使用教程r语言limma包教程 1. 制作三个矩阵2. 建模前归一化3. 建模及结果4.检查 #加载包和数据 if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager") if (!require("edgeR", quietly = TRUE)) BiocManager::install("edgeR") o ...
("LANGUAGE"="EN")# Set language of R message# Package download mirrors ---## For Bioconductor packagesoptions(BioC_mirror="https://mirrors.tuna.tsinghua.edu.cn/bioconductor")## For CRAN packages## Full list see mirrors on <https://cran.r-project.org/>options("repos"=c(CRAN="https:/...
It's a unoffical package, just for fun. I will put many simple R functions which used frequently in my daily data analysis, which should be useful for you too. Don't be worry to learn them, I'm used to write minimal function, just like perl, my favorate computer language ! function...
The package forproteomicslabelfreequantificationprolfqua(read : prolevka) evolved from a set of scripts and functions written in the R programming language to visualize and analyze mass spectrometric data, and some of them are still in R packages such as quantable, protViz or imsbInfer. For com...
The algorithm for calculating differentially expressed markers was based on the limma package [27], and this method was also integrated in the diffcyt package [28]. Strategies for pseudotime estimation and intermediate state calculation The algorithm used to estimate pseudotime was based on prior ...
Both approaches are based on the framework from the limma package [18]. Results include t-statistics, p values and standard errors. The p.Value is the associated p value and adj.P.Value is the p value adjusted by Benjamini and Hochberg’s method to control the false discovery rate [19]...