@@ -35,7 +35,6 @@ nSamples <- length(Biobase::sampleNames(bs))

 ```{r read_metrics,echo=FALSE,warning=FALSE,message=FALSE,fig.width=8, fig.height=7,fig.align='center'}

 # Methylation distribution for all the cells

 dat <- scmeth::readmetrics(bs)

-<<<<<<< HEAD

 SummaryTable <- dat

 SummaryTable$sample <- sub('\\..*$', '', SummaryTable$sample)

@@ -45,11 +44,8 @@ Summary_read <- summary(dat[,c('total','mapped','unmapped')])

-=======

-o <- order(dat$total,dat$sample)

-sampleOrder <- dat$sample[o]

-   

->>>>>>> upstream/master

+

+

 m <- reshape2::melt(dat[,c("sample","mapped","unmapped")], id.vars="sample",

                     variable.name="Mapping_status")

 m$sample <- factor(m$sample,levels=sampleOrder)

@@ -130,11 +126,9 @@ g

 ```{r bs_conversion,echo=FALSE,warning=FALSE,message=FALSE,fig.height=5,fig.width=5,fig.align='center'}

 bscDf <- scmeth::bsConversionPlot(bs)

-<<<<<<< HEAD

+

 SummaryTable$Bisulfite.converion.Rate <- round(bscDf$bsc,4)

-=======

->>>>>>> upstream/master

 g <- ggplot2::ggplot(bscDf, ggplot2::aes_string(x="''", y='bsc'))

 g <- g+ggplot2::geom_boxplot()

 g <- g+ggplot2::ylim(max(min(bscDf$bsc)-0.02,0),min(max(bscDf$bsc)+0.02,1))