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GuangchuangYu / subview.md
Last active Aug 26, 2015
embed subview in ggplot2
View subview.md
require(grid)
require(ggplot2)
require(magrittr)

theme_transparent <- function(...) {
    theme(panel.background = element_rect(
              fill = "transparent",
              colour = NA),
          plot.background = element_rect(
View emacs.md
View ttest.R
## http://ygc.name/2012/05/29/t-test/
p1 <- rnorm(1000)
p2 <- rnorm(1000, sd=3)
hist(p2, col="green", xlab="", main="")
hist(p1, col="red", add=T)
legend(legend=c("sd=1", "sd=3"), fill=c("green", "red"), x="topright")
View vennplot.R
x <- read.csv("/Volumes/YGC/Researches/ARCHIVE/Others/AL-1-by-GR.Yan/2D-data-and-analysis-result/2D.csv")
eg <- as.character(x[,1])
require(clusterProfiler)
xx <- enrichGO(eg, ont="BP")
gg <- xx@geneInCategory
names(gg) <- clusterProfiler:::TERM2NAME.BP(names(gg))
g <- gg[1:4]
require(gplots)
vm <- venn(g)
@GuangchuangYu
GuangchuangYu / bootstrapEnrichment.R
Created May 2, 2012
bootstrap method for enrichment analysis
View bootstrapEnrichment.R
# http://ygc.name/2012/04/29/bootstrap-for-enrichment-analysis/
goboot <- cmpfun(function(goid,
sampleSize,
nboot=1000) {
ratio <- rep(0, nboot)
allgene <- unique(mappedkeys(org.Hs.egGO))
allgeneInCategory <- unique(get(goid, org.Hs.egGO2ALLEGS))
@GuangchuangYu
GuangchuangYu / point_in_circle.R
Created Apr 28, 2012
get points within a circle
View point_in_circle.R
set.seed(123)
x <- rnorm(100)
y <- rnorm(100)
points.df <- data.frame(x=x,y=y)
center <- c(0.2, 0.3)
diameter <- 2
d <- apply(points.df, 1, function(x) x-center)
@GuangchuangYu
GuangchuangYu / qqplot.R
Created Apr 23, 2012
quantile quantile plot
View qqplot.R
## http://ygc.name/2011/08/02/q-q-plots/
qqplot <- function(y, distribution=qnorm) {
x <- distribution(ppoints(y))
plot(x, sort(y),
xlab="Theoretical Quantiles",
ylab="Sample Quantiles",
main="Normal Q-Q Plot"
)
lines(y,y)
@GuangchuangYu
GuangchuangYu / Antithetic_variates.R
Created Feb 29, 2012
The antithetic variates method is a variance reduction technique used in Monte Carlo methods.
View Antithetic_variates.R
## Antithetic sampling reframes our estimate as a sum of negatively
## correlated random variables, using the fact that negative
## correlation reduces the variance of a sum.
## http://en.wikipedia.org/wiki/Antithetic_variates
g <- function(x) 1/(1+x)
N <- 1500
n <- 50
u1 <- matrix(runif(2 * n * N), ncol = n)
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