nsheff/dipPeak
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dipPeak DipPeak is a kernel density estimator for high-throughput sequencing data. Please see the R documentation for additional details. ################################################################################ #HOW TO INSTALL dipPeak relies on 2 other R packages I wrote. You can get the latest source from github (these are public). #There are 2 ways to install dipPeak and its dependencies. #1. The easy way: install directly from github into R: require(devtools) install_github("sheffien/IRangeKernels") #public install_github("sheffien/CWriteR") #public install_github("sheffien/dipPeak", "YOUR_USERNAME", auth_token="YOUR PAT") #private #Create your PAT (personal access token) here: https://github.com/settings/applications #2. The hard way: you can clone the repos and then install locally, instead of directly from github. Here are some basic commands to go this route: #Get public repos: git clone http://github.com/sheffien/IRangeKernels.git git clone http://github.com/sheffien/CWriteR.git #then get the dipPeak source. (This is still private so you will have to have an ssh key set up to clone in this way). git clone git@github.com:sheffien/dipPeak.git #Once you have these, start R and install them. R install.packages("path/to/IRangeKernels", repos=NULL) install.packages("path/to/CWriteR", repos=NULL) install.packages("path/to/dipPeak", repos=NULL) ################################################################################ #HOW TO UPDATE #If you installed by cloning repos, can update later with git pull: cd dipPeak git pull #If you installed directly from github with install_github, just reinstall to update. ################################################################################ #HOW TO RUN #You have 2 options: Use a helper script to run on the command line, or run from within R directly. #1 ON THE COMMAND LINE #To use the command-line runner, you must have the R package "optparse" installed. install.packages("optparse") #You can then run it on the command line like this to see options: ./dipPeakRunner.sh #2 DIRECTLY FROM WITHIN R #You can load the package and run from within R like so: library(dipPeak) ?dipPeaks ################################################################################ #Some Misc Documentation: #By default, dipPeak estimates the peak detection cutoff #using all data, instead of a different cutoff based on each #individual chromosome. This is highly recommended, since sometimes single #chromosome cutoffs can lead to weird results.
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Kernel density estimator for DNase data.
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