## ----setup, include=FALSE----------------------------------------------------- knitr::opts_chunk$set(echo = TRUE) ## ----installation of package Cogito, eval=FALSE------------------------------- # BiocManager::install("Cogito") # library("Cogito") ## ----load package, echo = FALSE, message = FALSE------------------------------ library("Cogito", quietly = TRUE, verbose = FALSE) ## ----murine example data set RNA---------------------------------------------- head(MurEpi.RNA.small[, 1:3]) ## ----murine example data set RRBS--------------------------------------------- head(MurEpi.RRBS.small[, 1:3]) ## ----murine example data set ChIP--------------------------------------------- head(MurEpi.ChIP.small[[1]]) ## ----workflow aggregateRanges with small murine data set---------------------- mm9 <- TxDb.Mmusculus.UCSC.mm9.knownGene::TxDb.Mmusculus.UCSC.mm9.knownGene example.dataset <- list(ChIP = MurEpi.ChIP.small, RNA = MurEpi.RNA.small, RRBS = MurEpi.RRBS.small) aggregated.ranges <- aggregateRanges(ranges = example.dataset, organism = mm9, name = "murine.example") ## ----workflow result genes of aggregateRanges with small murine data set------ head(aggregated.ranges$genes[, c(1, 2:3, 13:14, 27:28)]) ## ----workflow result 1 genes of aggregateRanges with small murine data set---- lapply(aggregated.ranges$config$technologies, head, 3) head(lapply(aggregated.ranges$config$conditions, head, 3), 3) ## ----workflow summarizeRanges with small murine data set, eval=FALSE---------- # summarizeRanges(aggregated.ranges = aggregated.ranges) ## ----session info, echo = FALSE----------------------------------------------- sessionInfo()