Correlation tests, correlation matrix, and corresponding visualization methods in R (forward)

https://rstudio-pubs-static.s3.amazonaws.com/240657_5157ff98e8204c358b2118fa69162e18.html

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R drawing png with high resolution

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,[......]

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fasta2nexus by R script

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[......]

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Remove grid and background from plot (ggplot2)

HOMECATEGORIESTAGSMY TOOLSABOUTLEAVE MESSAGERSS2013-11-27 | 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[......]

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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 science-related material. This invariably raises questions, involving oth[……]

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1. 确定自变量与Y是否相关

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 p-value associated with the F-statistic using this distribution. Based on this p-value, we can determine whether or not to reject H0. （用[……]

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R pheatmap

> 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(dat[……]