Table of Contents
PyPop (Python for
Population Genomics) is an environment developed at
UC Berkeley for doing large-scale population genetic analyses
conformity to Hardy-Weinberg expectations
tests for balancing or directional selection
estimates of haplotype frequencies and measures and tests of significance for linkage disequilibrium (LD).
PyPop 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, 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.
PyPop was originally developed for
the analysis of data for the 13th International Histocompatiblity
Workshop and Conference held in Seattle, Washington in
2002 (Meyer et al. 2007,
Single et al. 2007a, Single et al. 2007a). For more details on
the design and technical details of
PyPop, please consult Lancaster et al. (2003), Lancaster et al. (2007a) and Lancaster et al. (2007b).