The scripting environment in SVS 7 allows for cross-communication between the powerful Python scripting language and the tools used in data analysis. Scripting is often the most effective way to make new features available to customers prior to new software releases. We often write scripts based on a specific customer’s need and then expand availability to all customers, many who could be dealing with similar issues. Another cool feature is that anyone, not just GHI employees, can write scripts to effectively accomplish their goals in SVS 7.
In this blog post, I would like to highlight some of the newest scripts available for SVS 7 users. Two of the new scripts were written by Golden Helix employees and two were written collaboratively by SVS users, Joost W. Morsink and Sander W. van der Laan from University Medical Center Utrecht. At Golden Helix, we love to see our customers take such an invested interest in making our software more effective, and we’d like to send a big thanks to Joost and Sander for all of their hard work!
Below you will find an introduction to the featured scripts. For more detailed documentation and download links, see our Script Repository page.
Joost and Sander wrote two scripts: Activate ATCG SNPs to flip strand and Activate ATCG SNPs to exclude SNPs. These scripts allow the user to identify ambiguous SNPs, one of A/T, T/A, C/G or G/C, and then further segregate these SNPs based on a minor allele frequency threshold, specified by the user. For example, you could exclude SNPs with an MAF >= 0.4 or activate SNPs with a MAF < 0.4 to flip strand.
Another newly available script, Row Means Histogram, provides a way to review the distribution of mean segment intensities in a common CNV region. It is analogous to performing multivariate segmentation, but the segment is defined manually. This script takes the hassle out of manually inspecting a region of interest.
The last script featured in this blog post is Chi-Squared Contingency Table. This script assumes that the cell counts for the m-by-n contingency tables are contained in one row with columns specified for each group and outcome combination. The script then will calculate the chi-squared statistic and p-value for each row in the spreadsheet, allowing the user to simultaneously investigate several m x n tables.
We hope that you find these new scripts helpful in your SVS workflows!
Share your scripts with the research community
If you have written any scripts and think they are useful to others, we encourage you to share them with the community. Just email a *.txt or *.py file to firstname.lastname@example.org with any accompanying documentation or special instructions. Once we test your script and check its validity, we’ll post it on our Add-on Scripts Repository for others to download.