FORK NOTE: this fork created due to a few problems concerning Thor (only) and certain data sets being run. These issue are:

• dependency on older hmmlearn module (<2.0), can't this be looked at?

• may be related error fro Thor.py line 81, train_HMM

  report=options.report, poisson=options.poisson)

• two errors have originate in the train_hmm() function (which may be quite a big one) they are:
  • IndexError: cannot do a non-empty take from an empty axes.
  • ValueError: low >= high
• TMM normalization is attempted but doesn't succeed ... need verbose details on why not?
• No differential peaks detected ... when macs2 does find peaks ... not verbose enough ... need to know why

RESUME:

RGT is an open source python library for analysis of regulatory genomics. RGT is programmed in an oriented object fashion and its core classes provide functionality for handling regulatory genomics data.

The toolbox is made of a core library and several tools:

• THOR: ChIP-Seq differential peak caller, replaces ODIN
• Motif Analysis: TBFS match and enrichment
• HINT: DNase-Seq footprinting method
• RGT-Viz: Visualization tool
• TDF: DNA/RNA triplex domain finder

The quickest and easiest way to get RGT is to to use pip:

pip install --user RGT

This will install the full RGT suite with all dependencies. If you have errors, this is usually due to three dependencies that you can install beforehand:

pip install --user cython numpy scipy

Alternatively, you can clone this repository:

git clone https://github.com/CostaLab/reg-gen.git

or download a specific release, then proceed to manual installation:

cd reg-gen
python setup.py install --user

Detailed installation instructions and basic problem solving can be found at:

http://www.regulatory-genomics.org/rgt/download-installation