# plotHist: Plot the histogram of positive proportions In UofABioinformaticsHub/rnaCleanR: Calculate strandness information of a bam file

## Description

Plot the histogram of positive proportions of the input data frame coming from `getStrandFromBamFile`

## Usage

 ```1 2 3``` ```plotHist(windows, save = FALSE, file = "hist.pdf", groupBy = NULL, normalizeBy = NULL, split = c(10, 100, 1000), breaks = 100, useCoverage = FALSE, heatmap = FALSE, ...) ```

## Arguments

 `windows` data frame containing the strand information of the sliding windows. Windows can be obtained using the function `getStrandFromBamFile`. `save` if TRUE, then the plot will be save into the file given by `file` parameter `file` the file name to save to plot `groupBy` the columns that will be used to split the data. `normalizeBy` instead of using the raw read count/coverage, we will normalize it to a proportion by dividing it to the total number of read count/coverage of windows that have the same value in the `normalizeBy` columns. `split` an integer vector that specifies how you want to partition the windows based on the coverage. By default `split` = c(10,100,1000), which means that your windows will be partitionned into 4 groups, those have coverage < 10, from 10 to 100, from 100 to 1000, and > 1000 `breaks` an integer giving the number of bins for the histogram `useCoverage` if TRUE then plot the coverage strand information, otherwise plot the number of reads strand information. FALSE by default `heatmap` if TRUE, then use heat map to plot the histogram, otherwise use barplot. FALSE by default. `...` used to pass parameters to facet_wrap

## Value

If `heatmap=FALSE`: a ggplot object

`getStrandFromBamFile`, `plotWin`
 ```1 2 3``` ```bamfilein = system.file('extdata','s1.sorted.bam',package = 'strandCheckR') win <- getStrandFromBamFile(file = bamfilein,sequences='10') plotHist(win) ```