IronPython vs. Mako vs. Python vs. VarSeq Comparison Chart

It provides a familiar, non-XML syntax that compiles into Python modules for maximum performance. Mako's syntax and API borrows from the best ideas of many others, including Django and Jinja2 templates, Cheetah, Myghty, and Genshi. Conceptually, Mako is an embedded Python (i.e. Python Server Page) language, which refines the familiar ideas of componentized layout and inheritance to produce one of the most straightforward and flexible models available, while also maintaining close ties to Python calling and scoping semantics. As templates are ultimately compiled into Python bytecode, Mako's approach is extremely efficient and was originally written to be just as fast as Cheetah. Today, Mako is very close in speed to Jinja2, which uses a similar approach and for which Mako was an inspiration. Can access variables from their enclosing scope as well as the template's request context

Simple, fast, and repeatable variant analysis software for gene panels, exomes, and whole genomes. VarSeq is an intuitive, integrated software solution for tertiary analysis. With VarSeq you can automate your workflows and analyze variants for gene panels, exomes, and whole genomes. Understanding genomic data has never been easier thanks to our software. VarSeq software provides a powerful filtering and annotation engine to sift through large variant data sets. Using a chain of filters, you can quickly narrow your list of variants down to those that are most likely to be of interest. After determining the parameters that work well for your analysis, you can save the state of your filters so that you can easily apply the same analysis to another dataset. The same automated workflow can be used for each batch of samples, making VarSeq an ideal solution for high-throughput environments. Real-time filtering gives you the power to quickly prototype and tune analysis workflows.