David Ruau bobthecat
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| library(rbenchmark) | |
| res <- benchmark( cosine(mat), | |
| cosineRcpp(mat), | |
| columns=c("test", "replications", "elapsed", | |
| "relative", "user.self", "sys.self"), | |
| order="relative", | |
| replications=1000) | |
| res | |
| test replications elapsed relative user.self sys.self |
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| library(twitteR) | |
| library(ggplot2) | |
| library(grid) | |
| # download all that you can | |
| pol <- userTimeline('BeijingAir', n=3200) | |
| length(pol) | |
| # 3200 | |
| myGrep <- function(x){ |
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| library(twitteR) | |
| library(ggplot2) | |
| library(grid) | |
| # download all that you can | |
| pol <- userTimeline('BeijingAir', n=3200) | |
| length(pol) | |
| # 3200 | |
| myGrep <- function(x){ |
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| library(GEOquery); library(RankProd); library(mouse4302.db) | |
| ## Download the data from GEO | |
| gse12499 <- getGEO('GSE12499',GSEMatrix=TRUE) | |
| e <- exprs(gse12499[[1]]) | |
| dim(e) | |
| [1] 45101 10 |
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| ### R code from vignette source 'Presentation.Rnw' | |
| ### Encoding: UTF-8 | |
| ################################################### | |
| ### code chunk number 1: init | |
| ################################################### | |
| options(width=60) | |
| ################################################### |
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| ### R code from vignette source 'Presentation_2.Rnw' | |
| ### Encoding: UTF-8 | |
| ################################################### | |
| ### code chunk number 1: init | |
| ################################################### | |
| options(width=60) | |
| ################################################### |
bobthecat
/ religion_index.r
Created
September 21, 2012 18:37
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| library(xlsx) | |
| library(googleVis) | |
| # I downloaded the Excel file, cleaned the headers and worked a bit | |
| # the column title. | |
| da <- read.xlsx("~/Downloads/religion.xlsx", sheetName=1) | |
| rownames(da) <- da$COUNTRY. | |
| da <- da[,-1] | |
| religion <- data.frame(country=rep(rownames(da), 3), | |
| year=c(rep(2007, dim(da)[1]), rep(2009, dim(da)[1]), rep(2010, dim(da)[1])), | |
| GRI=c(da$GRI_2007, da$GRI_2009, da$GRI_2010), |
bobthecat
/ getting_some_data.r
Created
December 20, 2012 18:19
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| library(GEOquery) | |
| ## Download the data from GEO | |
| GDS3716 <- getGEO('GDS3716') | |
| # transform the GDS to and expressionSet | |
| eset <- GDS2eSet(GDS3716,do.log2=TRUE) | |
| phenoData <- pData(eset) | |
| # keep only the ER+ and ER- | |
| samples <- phenoData$sample[grep("ER", phenoData$specimen)] | |
| # subsetting the expressionSet | |
| eset <- eset[,samples] |
bobthecat
/ empirical_FDR.r
Last active
December 9, 2015 23:58
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| ## EXTRACTING CLASS LABELS | |
| classLabel <- sub("^ER(.*) breast cancer", "\\1", grep("ER", phenoData$specimen, value=T)) | |
| classLabel | |
| [1] "-" "-" "-" "-" "-" "-" "-" "-" "-" "+" "+" "+" "+" "+" "+" "+" "+" "+" | |
| ## COMPUTING P-VALUE DISTRIBUTION | |
| minus = which(classLabel=="-") | |
| plus = which(classLabel=="+") | |
| p <- apply(e, 1, function(x){t.test(as.numeric(x[minus]), as.numeric(x[plus]))$p.value}) |
bobthecat
/ empirical_FDR.r
Last active
December 9, 2015 23:58
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| ## LOADING LIBRARIES FOR PARALLEL PROCESSING | |
| library(doMC) | |
| ncore = multicore:::detectCores() | |
| registerDoMC(cores = ncore) | |
| ## COMPUTING THE RANDOM P-VALUE DISTRIBUTION | |
| # How many random sampling | |
| R=100 | |
| # Shuffling the sample labels and recomputing the p-value each time | |
| p.rand <- foreach(i = 1:dim(e)[1], .combine=rbind) %dopar% { |