pepbedr's Introduction

PepBedR

Introduction

PepBedR: is a R package to process bed and bigBed files from peptide evidences.

Installing pepBed

First we need to install devtools:

  install.packages("devtools")
  library(devtools)

Then, we can install the package using:

  install_github("bigbio/PepBedR")
  library(PepBedR)

Report Examples

Some examples to test the package are provided here. (additional work in process...)

Process BigBed

For some functionalities, PepBedR runs internally some tools from UCSC. To install the UCSC utilities, follow the instructions here.

Alternatively, you could run from terminal the commands below to get installed the requiered binaries (tested on Ubuntu 16.04):

  cd $HOME
  
  # make directory
  mkdir kent-utils
  
  cd kent-utils
  
  # download binaries from UCSC
  curl -O http://hgdownload.soe.ucsc.edu/admin/exe/linux.x86_64/bigBedToBed
  curl -O http://hgdownload.soe.ucsc.edu/admin/exe/linux.x86_64/bigBedSummary
  curl -O http://hgdownload.soe.ucsc.edu/admin/exe/linux.x86_64/bigBedInfo
  
  # set exec permission
  chmod -R a+x .
  
  # Add the follow line to the .profile file. 
  # You could need to reboot your system to take effect of the changes.
  export PATH=$PATH:$HOME/kent-utils

Note that for Mac OS system, the binaries can be download from here.

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pepbedr's Issues

Phosphorylation probability

We need to provide a "global" probability score around each phosphorylation site.
Crosstalk phosphorylation score should be computed.

Report RMd script

@enriquea I have created a simple script https://github.com/bigbio/PepBedR/blob/master/scripts/pepbedDescription.Rmd This should take a bed file as input and generate a PDF with the report of the data. First for the non-modified bed files.

Review library for the future

https://www.bioconductor.org/packages/devel/bioc/vignettes/Sushi/inst/doc/Sushi.pdf

Compare the number of modified peptide with non modified.

For the following example:

ftp://ftp.pride.ebi.ac.uk/pride/data/cluster/trackhubs/2017-10/hg38/

We have two files there Modified and non modified peptides mapped to the Genome Coordinates. We would like to know:

The region of the genome with more modified peptides? The region of the genome with more modified peptides by specific modifications (phospho, etc.). In the example we have generated, each modified peptides contains a different color.