+ Source code
PyPop (Python for Population Genomics) is an environment developed by the Thomson lab for doing large-scale population genetic analyses including: (1) conformity to Hardy-Weinberg expectations, (2) tests for balancing or directional selection; (3) estimates of haplotype frequencies (and their distributions) and measures and tests of significance for linkage disequilibrium (LD).
It is an object-oriented framework implemented in the programming language Python. Python is a flexible scripting language which allows rapid prototyping of code and has powerful features for interfacing with other languages, such as C (in which we have already implemented many routines and which is particularly suited to computationally intensive tasks).
The output of the analyses are stored in the XML format (XML is the eXtensible Markup Language devised by the World Wide Web Consortium, and is a platform-independent, vendor-neutral, non-proprietary, open standard for storing data). These output files can then be transformed using standard tools into many other data formats suitable for machine input (such as PHYLIP or input for spreadsheet programs such as Excel or statistical packages, such as R, plain text, or HTML for human-readable format. Storing the output in XML allows the final viewable output format to be redesigned at will, without requiring the (often time-consuming) re-running of the analyses themselves.
An outline of PyPop can be found in our 2007 Tissue Antigens and 2003 PSB papers.
Beta binary versions of PyPop are now publicly available (see "Getting and installing PyPop" link below for links to the current binaries) for both:
yum install pypop
Both binary packages are approximately 5.5 Mb downloads.
PyPop is free software (sometimes referred to as open source software) and the source code is released under the terms of the "copyleft" GNU General Public License, or GPL (http://www.gnu.org/licenses/gpl.html). This means even if we haven't compiled a binary for your platform, it is possible for you to download the source code and compile it yourself.
Documentation for PyPop is contained in the PyPop User Guide.
Please be aware that this is a beta release so it is highly likely that there may be bugs and wrinkles to iron out. Please direct all questions to Alex Lancaster at the address below.
When citing PyPop, please cite our most recent (2007) paper from Tissue Antigens:
In addition, you can also cite our 2003 Pacific Symposium on Biocomputing paper:
Population data files and online supporting materials for published studies listed in the Solberg et al. meta-analysis paper may be found here.
PyPop is affiliated with ImmPort.org, the Immunology Database and Analysis Portal. The ImmPort system provides advanced information technology support in the production, analysis, archiving, and exchange of scientific data for the diverse community of life science researchers supported by NIAID/DAIT. The development of the ImmPort system was supported by the NIH/NIAID Bioinformatics Integration Support Contract (BISC), Phase II.
This work has benefited from the support of NIH grant AI49213 (13th IHW) and NIH/NIAID Contract number HHSN266200400076C N01-AI-40076. Thanks to Steven J. Mack, Kristie A. Mather, Steve Marsh, Mark Grote and Leslie Louie for helpful comments and testing.