Managing large SNP datasets with SNPpy.

Using relational databases to manage SNP datasets is a very useful technique that has significant advantages over alternative methods, including the ability to leverage the power of relational databases to perform data validation, and the use of the powerful SQL query language to export data. SNPpy is a Python program which uses the PostgreSQL database and the SQLAlchemy Python library to automate SNP data management. This chapter shows how to use SNPpy to store and manage large datasets.

SNPpy--database management for SNP data from genome wide association studies.

Background: We describe SNPpy, a hybrid script database system using the Python SQLAlchemy library coupled with the PostgreSQL database to manage genotype data from Genome-Wide Association Studies (GWAS). This system makes it possible to merge study data with HapMap data and merge across studies for meta-analyses, including data filtering based on the values of phenotype and Single-Nucleotide Polymorphism (SNP) data. SNPpy and its dependencies are open source software.

The Multiscale Systems Immunology project: software for cell-based immunological simulation.

Background: Computer simulations are of increasing importance in modeling biological phenomena. Their purpose is to predict behavior and guide future experiments. The aim of this project is to model the early immune response to vaccination by an agent based immune response simulation that incorporates realistic biophysics and intracellular dynamics, and which is sufficiently flexible to accurately model the multi-scale nature and complexity of the immune system, while maintaining the high performance critical to scientific computing.