A paper on ESPERR was published in Genome Research on 19 October 2006, and is available online

ESPERR 7 species RP Scores

These scores are currently available for the two most recent builds of human and of mouse.

They are avaailable in the UCSC genome browser as "Reg Potential 7 species" in the "Expression and Regulation" track group

Raw scores are in UCSC wiggle track format, and are available both as full range log odds scores (*.scores.bz2) and truncated so that all negative scores are set to zero (*.scores.truncated.bz2).

Software

Code is available via anonymous svn. It can be checked out by:

svn co http://coltrane.bx.psu.edu/svn/esperr/trunk/ esperr-trunk

Turnkey template

A template Makefile that can be easily modified to run the ESPERR procedure on arbitrary training data is available in svn under the training_template directory. It requires that the software listed below be built and installed in some location.

ESPERR

The python code is in the directory 

esperr-main
and can be built with the standard tools (see the README).

This code requires:

  • Python 2.4
  • Numeric python (currently this must be Numeric, everything will transition to the better maintained numpy in the near future)
  • Scipy (used only for matrix math in the inferrence of ancestral distributions)
  • Pyrex (needed to create C code and wrappers for the various models)
  • Pypar (optional, needed to use the MPI version)
  • The bx-python libraries (see below)

bx-python

The bx-python libraries used by this software are availabe here:

http://bitbucket.org/james_taylor/bx-python/