## ----setup, include=FALSE, cache=FALSE----------------------------------- require(knitr) # set global chunk options opts_chunk$set(fig.path='tmp/deepSNV-', fig.align='center', fig.show='hold', fig.width=4, fig.height=4, out.width='.4\\linewidth', dpi=150) options(replace.assign=TRUE,width=75) knit_hooks$set(nice = function(before, options, envir) { if (before) par(mar = c(4, 4, .1, .1), mgp=c(2.5,1,0), bty="n") }) ## ----echo=FALSE, results='asis'------------------------------------------ print(citation("deepSNV")[1], style="LaTeX") ## ------------------------------------------------------------------------ library(deepSNV) regions <- data.frame(chr="B.FR.83.HXB2_LAI_IIIB_BRU_K034", start = 2074, stop=3585) ## ------------------------------------------------------------------------ # HIVmix <- deepSNV(test = "http://www.bsse.ethz.ch/cbg/software/deepSNV/data/test.bam", # control = "http://www.bsse.ethz.ch/cbg/software/deepSNV/data/control.bam", # regions=regions, q=10) ## ------------------------------------------------------------------------ data(HIVmix) # Attach the data instead, as it could fail in routine checks without internet connection. show(HIVmix) ## ------------------------------------------------------------------------ control(HIVmix)[100:110,] test(HIVmix)[100:110,] ## ----HIV, nice=TRUE------------------------------------------------------ plot(HIVmix) ## ------------------------------------------------------------------------ SNVs <- summary(HIVmix, sig.level=0.05, adjust.method="BH") head(SNVs) nrow(SNVs) min(SNVs$freq.var) ## ------------------------------------------------------------------------ sum(RF(test(HIVmix), total=T) > 0.01 & RF(test(HIVmix), total=T) < 0.95) ## ------------------------------------------------------------------------ data(trueSNVs, package="deepSNV") table(p.adjust(p.val(HIVmix), method="BH") < 0.05, trueSNVs) ## ----phiX, dev="jpeg", nice=TRUE----------------------------------------- ## Load data (unnormalized) data(phiX, package="deepSNV") plot(phiX, cex.min=.5) ## Normalize data phiN <- normalize(phiX, round=TRUE) plot(phiN, cex.min=.5) ## ----pval, nice=TRUE----------------------------------------------------- p.norm <- p.val(phiN) n <- sum(!is.na(p.norm)) qqplot(p.norm, seq(1/n,1, length.out=n), log="xy", type="S", xlab="P-value", ylab="CDF") p.val <- p.val(phiX) points(sort(p.val[!is.na(p.val)]), seq(1/n,1, length.out=n), pch=16, col="grey", type="S", lty=2) legend("topleft", c("raw data", "normalized data"), pch=16, col=c("grey", "black"), bty="n", lty=3) abline(0,1) ## ----dev="jpeg", nice=TRUE----------------------------------------------- data("RCC", package="deepSNV") show(RCC) plot(RCC, cex.min=.5) RCC.bb = estimateDispersion(RCC, alternative="two.sided") plot(RCC.bb, cex.min=.5) ## ------------------------------------------------------------------------ RCC.bb@log.lik RCC@log.lik RCC.bb@log.lik - RCC@log.lik log(4*nrow(test(RCC))) ## ------------------------------------------------------------------------ summary(RCC, adjust.method="bonferroni")[,1:6] ## ------------------------------------------------------------------------ tab <- summary(RCC.bb, adjust.method="bonferroni")[,1:6] tab ## ----echo=FALSE, results='asis'------------------------------------------ toLatex(sessionInfo())