
> library(gplots)
Attaching package: ‘gplots’
The following object is masked from ‘package:stats’:
lowess
> > setwd(“/home/zyshen/work/QM_nanjing”) > data2<read.csv(“combined_example.level_5.csv”, header=T, sep=”,”) > data2plot<data.matrix(data2[2:3]) > row.names(data2plot)<data2[,1] > heatmap.2(data2plot,trace=”none”,cexCol = 2,col=greenred(50), margins = c(5, 40), sepwidth=c(0.05,0.05))
if (!require(“gplots”)) { install.packages(“gplots”, dependencies = TRUE) library(gplots) } if (!require(“RColorBrewer”)) { install.packages(“RColorBrewer”, dependencies = TRUE) library(RColorBrewer) } […]
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Correlation tests, correlation matrix, and corresponding visualization methods in R Igor Hut 12 January, 2017 Install and load required R packages Methods for correlation analyses Compute correlation in R R functions Preliminary considerations Preleminary test to check the test assumptions Pearson correlation test Kendall rank correlation test Spearman rank correlation coefficient How to interpret […]
可重复的示例：
the_plot < function() { x < seq(0, 1, length.out = 100) y < pbeta(x, 1, 10) plot( x, y, xlab = “False Positive Rate”, ylab = “Average true positive rate”, type = “l” ) }
png( “test.png”, width = 3.25, height = 3.25, units = “in”, res = 1200, pointsize = 4 ) […]
Workspace loaded from ~/.RData] > setwd(“/home/shenzy/work/beast/51samples”) > library(seqinr) > data=read.fasta(“51strain_core_gene_alignment.aln”) > library(ape) Attaching package: ‘ape’ The following objects are masked from ‘package:seqinr’: as.alignment, consensus > write.nexus.data(data,file=”51strain_core_gene_alignment.aln.nexus”, format=”DNA”) > […]
Remove grid and background from plot (ggplot2) HOMECATEGORIESTAGSMY TOOLSABOUTLEAVE MESSAGERSS 20131127  category RStudy  tag ggplot2 Generate data library(ggplot2) a < seq(1, 20) b < a^0.25 df < as.data.frame(cbind(a, b)) basic plot myplot = ggplot(df, aes(x = a, y = b)) + geom_point() myplot
theme_bw() will get rid of the background myplot […]
Size Matters: Metabolic Rate and Longevity
John Tukey once said, “The best thing about being a statistician is that you get to play in everyone’s backyard.” I enthusiastically agree!
I frequently enjoy reading and watching sciencerelated material. This invariably raises questions, involving other “backyards,” that I can better understand using statistics. For instance, see my […]
1. 确定自变量与Y是否相关 证明：自变量X1，X2，….XP中至少存在一个自变量与因变量Y相关 For any given value of n（观测数据的数目） and p（自变量X的数目）, any statistical software package can be used to compute the pvalue associated with the Fstatistic using this distribution. Based on this pvalue, we can determine whether or not to reject H0. （用软件计算出的与Fstatistic 相关的pvalue来验证假设，the pvalue associated with the Fstatistic） 例子： Is there a relationship between […]
MSstats: an R package for statistical analysis of quantitative mass spectrometrybased proteomic experiments.
R PheWAS: data analysis and plotting tools for phenomewide association studies in the R environment.
> library(caTools); > library(bitops); > library(grid); > data=read.csv(“/home/shenzy/Desktop/R/Bac.heatmap1.csv”) > data=read.csv(“/home/shenzy/Desktop/R/Bac.heatmap1.2.csv”) > View(data) > data=read.csv(“/home/shenzy/Desktop/R/Bac.heatmap1.2.csv”,sep=”\t”) > View(data) > row.names(data) < data$X.OTU.ID; > View(data) > data_matrix<data[,2:15] > View(data_matrix) > data_matrix<data[,2:14] > View(data_matrix) > View(data) > data_matrix<data[,1:14] > View(data_matrix) > library(pheatmap) > data_matrix[is.na(data_matrix)]<1 > View(data_matrix) > data_log10<log10(data_matrix) > View(data_log10) > data_log2<log2(data_matrix) > View(data_log2) > pheatmap(data_log2,fontsize=9, fontsize_row=6) > pheatmap(data_log2, […]


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