## ----message=FALSE, results="hide"-------------------------------------------- library(sesame) sesameDataCache() ## ----qc1, eval=FALSE---------------------------------------------------------- # ## calculate metrics on all IDATs in a specific folder # qcs = openSesame(idat_dir, prep="", func=sesameQC_calcStats) ## ----echo=FALSE--------------------------------------------------------------- library(knitr) kable(data.frame( "Short Key" = c( "detection", "numProbes", "intensity", "channel", "dyeBias", "betas"), "Description" = c( "Signal Detection", "Number of Probes", "Signal Intensity", "Color Channel", "Dye Bias", "Beta Value"))) ## ----qc2---------------------------------------------------------------------- sdfs <- sesameDataGet("EPIC.5.SigDF.normal")[1:2] # get two examples ## only compute signal detection stats qcs = openSesame(sdfs, prep="", func=sesameQC_calcStats, funs="detection") qcs[[1]] ## ----qc3---------------------------------------------------------------------- sesameQC_getStats(qcs[[1]], "frac_dt") ## ----qc4---------------------------------------------------------------------- ## combine a list of sesameQC into a data frame head(do.call(rbind, lapply(qcs, as.data.frame))) ## ----qc5, message=FALSE------------------------------------------------------- sdf <- sesameDataGet('EPIC.1.SigDF') qc = openSesame(sdf, prep="", func=sesameQC_calcStats, funs=c("detection")) ## equivalent direct call qc = sesameQC_calcStats(sdf, c("detection")) qc ## ----qc6, echo=FALSE---------------------------------------------------------- options(rmarkdown.html_vignette.check_title = FALSE) ## ----qc7---------------------------------------------------------------------- sdf <- sesameDataGet('EPIC.1.SigDF') qc <- sesameQC_calcStats(sdf, "intensity") qc sesameQC_rankStats(qc, platform="EPIC") ## ----------------------------------------------------------------------------- sessionInfo()