revert 3738e7e

Author: lishen

README.md

@@ -70,13 +70,12 @@ You need R version >= 2.15.0 and Python 2.7 to be able to use ngs.plot. Please a
    biocLite( "BSgenome" )
    biocLite( "Rsamtools" )
    biocLite( "ShortRead" )
-   biocLite( "GenomicFiles" )
    ```
 
 1. (Optional) Install ngsplot package in Galaxy: read the `galaxy/README.txt` for instructions. A wiki will be provided to demonstrate the workflow of ngs.plot in Galaxy.
 
 # USAGE
-A wiki-page has been created for detailed explanation of each argument: [ProgramArguments101](https://github.com/shenlab-sinai/ngsplot/wiki/ProgramArguments101). Quick tip: when you type one of the commands without specifying any argument, the program will print out a brief usage.
+A wiki-page has been created for detailed explanation of each argument: [ProgramArguments101](https://github.com/shenlab-sinai/ngsplot/wiki/ProgramArguments101). Quick tip: when you type one of the commands without specifying any argument, the program will print out a brief usage. 
 
 ## Manipulate annotation database and the use of option "-F"
 The `ngsplotdb.py` script is easy to use. Here are a few examples:
@@ -201,7 +200,7 @@ Usage: plotCorrGram.r -I ngsplot_output.zip -O output_name [Options]
       ```
       The avgprof and heatmap plotted by ngs.plot like this:
 
-      ![hesc.k27.genebody.all.png](./webimgs/hesc.k27.genebody.all.png)
+      ![hesc.k27.genebody.all.png](./webimgs/hesc.k27.genebody.all.png) 
 
    For all the above examples, data are from: **ENCODE Project Consortium, et al. (2012). An integrated encyclopedia of DNA elements in the human genome. Nature 489, 57-74.**
 

lib/coverage.r

@@ -419,10 +419,6 @@ REDUCEsampler.ngsplot <- function(sampleSize=500, verbose=FALSE){
 # Adapted from Martin Morgan's post:
 # https://support.bioconductor.org/p/64231/
 # Require library: GenomicFiles
-# Args:
-#   sampleSize: reads sampled from bam file.
-#   verbose: turn on verbose output.
-
     tot <- 0L
     function(x, y, ...) {
         if (length(x) < sampleSize)
@@ -459,7 +455,7 @@ estiMapqStyle <- function(bam.file){
     sbp <- ScanBamParam(what=sbw, flag=scanBamFlag(
                         isUnmappedQuery=F, isDuplicate=F))
     samp <- BamFile(bam.file, yieldSize=500)
-    yield <- function(x) readGAlignments(x, param=sbp)
+    yield <- function(x) readGAlignments(x, param=ScanBamParam(what=sbw))
     map <- identity
     samp.reads <- reduceByYield(samp, yield, map, REDUCEsampler.ngsplot(500, FALSE))
     samp.len <- length(samp.reads)