## ---- echo = FALSE, message = FALSE------------------------------------------- library(ctsGE) library(pander) library(rmarkdown) ## ----eval=FALSE,warning=FALSE,message=FALSE----------------------------------- # if (!requireNamespace("BiocManager", quietly=TRUE)) # install.packages("BiocManager") # BiocManager::install("ctsGE") ## ----eval=FALSE,message=FALSE, warning=FALSE---------------------------------- # library(GEOquery) # # gse2077 <- getGEO('GSE2077') # gseAssays <- Biobase::assayData(gse2077) # gseExprs <- Biobase::assayDataElement(gseAssays[[1]][,c(1:6)],'exprs') # # # list of the time series tables use only 6 samples # gseList <- lapply(1:6,function(x){data.frame(Genes = rownames(gseExprs),Value = gseExprs[,x])}) # names(gseList) <- colnames(gseExprs) ## ----eval=FALSE,message=FALSE,warning=FALSE----------------------------------- # rts <- readTSGE(gseList,labels = c("0h","6h","12h","24h","48h","72h")) ## ---- message=FALSE,warning=FALSE--------------------------------------------- data_dir <- system.file("extdata", package = "ctsGE") files <- dir(path=data_dir,pattern = "\\.xls$") ## ----message=FALSE,warning=FALSE---------------------------------------------- rts <- readTSGE(files, path = data_dir, labels = c("0h","6h","12h","24h","48h","72h") ) ## ----message=FALSE,warning=FALSE---------------------------------------------- names(rts) rts$timePoints head(rts$samples) head(rts$tags) ## ---- echo=FALSE,results='asis'----------------------------------------------- panderOptions("table.style","rmarkdown") pander(head(rts$tsTable)) ## ----message=FALSE,warning=FALSE---------------------------------------------- prts <- PreparingTheIndexes(x = rts, min_cutoff=0.5, max_cutoff=0.7, mad.scale = TRUE) ## ----message=FALSE,warning=FALSE---------------------------------------------- prts$cutoff ## ----message=FALSE,warning=FALSE,echo=FALSE----------------------------------- library(dplyr) count_zero <- function(x){ sum(strsplit(x,"")[[1]]==0)} tbl <- prts$index %>% # counting genes at each index group_by(index)%>% summarise(size=length(index)) %>% # counting the number of zeros at each index group_by(index)%>% mutate(nzero=count_zero(as.character(index))) %>% # groups genes by the number of zeros and sum them group_by(nzero) %>% summarise(genes=round(sum(size)/12625,1)) tmp = which(0:6%in%tbl$nzero==0)-1 tmp_df = data.frame(nzero=tmp,genes=rep(0,length(tmp))) tbl <- bind_rows(tbl,tmp_df) %>% arrange(nzero) labs <- seq(0,max(tbl$genes), by = 0.2) barplot(tbl$genes, main = paste("Number of zeros in indexes with cutoff =",prts$cutoff), names.arg = tbl$nzero,axes = FALSE, xlab="Number of Zeros") axis(side = 2, at = labs, labels = paste0(labs * 100, "%")) ## ---- message=FALSE,warning=FALSE--------------------------------------------- prts <- PreparingTheIndexes(x = rts, mad.scale = TRUE) names(prts) ## ----message=FALSE,echo=FALSE,warning=FALSE,results="asis"-------------------- panderOptions("table.style","simple") pander(head(prts$scaled)) ## ----message=FALSE,echo=FALSE,warning=FALSE,results="asis"-------------------- panderOptions("table.style","simple") pander(head(prts$index)) ## ----message=FALSE, warning=FALSE,eval=FALSE---------------------------------- # ClustIndexes <- ClustIndexes(prts, scaling = TRUE) # names(ClustIndexes) # # table of the index and the recommended k that were found by the function # head(ClustIndexes$optimalK) # # # Table of clusters index for each gene # head(ClustIndexes$ClusteredIdxTable) ## ----message=FALSE,warning=FALSE---------------------------------------------- indexPlot <- PlotIndexesClust(prts,idx = "1100-1-1",scaling = TRUE) names(indexPlot) ## ----message=FALSE,warning=FALSE,echo=FALSE----------------------------------- length(indexPlot$graphs) ## ----message=FALSE,warning=FALSE,results="asis",echo=FALSE-------------------- panderOptions("table.style","rmarkdown") pander(head(indexPlot[[1]])) ## ----message=FALSE,warning=FALSE---------------------------------------------- indexPlot$graphs ## ----message=FALSE,warning=FALSE,eval=FALSE----------------------------------- # library(shiny) # library(DT) # ctsGEShinyApp(rts)