A common trade-off faced by program and tool developers is providing the convenience of a Graphical User Interface (GUI) with the raw power and automation of command-line oriented programs. Often, flexibility of tool use and data manipulation is sacrificed for informative visual displays and interactive dialogs. SVS delivers a unique solution to not only take advantage of these two paradigms but also open the way for cross-communication between other tools used in data analysis.
Browse the Script Repository or Request a Script
Browse our script repository for a number of useful scripts from importing specific data formats to advanced analysis applications and more. Don't see what you need? Let us know what you're looking for and we'll see how we can help.
What are Python Scripts?
Python scripts are essentially pieces of code that can be written and run without having to be compiled into the software. This enables anyone familiar with Python to quickly and easily extend SVS in a number of ways including, integrating with other command line programs (MACH, PLINK, etc.), automating a series of workflows, building custom analysis operations, and more. Python itself is a clear and powerful object-oriented programming language, comparable to Perl, Ruby, Scheme, or Java. It's relatively easy to learn and scripts written in Python are intuitive to read.
NumPy and SciPy
Included with Python in SVS are the mature statistical and numeric methods packages of NumPy and SciPy, giving SVS a broad base of standardized test statistics and linear algebra. Now both you and our own bioinformaticians supporting you can quickly adapt methods and build custom analyses to solve any unique challenges you encounter. Combined with the powerful interactive features of SVS, Python scripts using these packages are first class features with polished interfaces, interactions and logging support.
Python Script Editor
A fully integrated Python script editor enables you to quickly read, write, or edit scripts. It comes complete with automatic formatting and integrated command help. Upon finishing a script, just save it in the appropriate folder and the script will appear in the appropriate menu within the actual user interface, or spreadsheet column to which it applies. This enables those well versed in scripting to provide custom point-and-click features to their colleagues.
The Python Shell gives you access to analysis views programmatically while running in GUI mode. This feature is most useful for casual interaction with the program, such as running quick scripts, trying out new commands, or testing scripts.
Want to Learn Python?
Here are some resources to help you get started taking advantage of the power of scripting.