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Welcome to the SplAdder wiki. Here you will learn more about the details of the SplAdder pipeline, how to apply it to your data, how to choose parameters well suited for the kind of question you would like to answer, or how to use and visualize the output data. SplAdder is a work in progress and currently in alpha state. However, it has been used and tested in various research projects of varying scale, ranging from a few samples of A. thaliana to thousands of human samples.

This wiki will hopefully accumulate more and more content over time. If you have specific questions, suggestions or any other kind of feedback, please send me an e-mail or use the Issue tracker to contact me. This wiki is currently in its built up phase - several links might not be operational yet. However, this should change over the next days / weeks. Please check back to find more complete content in the future.

All information in this wiki refer to the python version of SplAdder as this is where future development will take place. However, most of the content should also apply to the Matlab version and both versions produce identical results for now. Note, that the results of Matlab version and python version can not be used interchangeably when using hdf5 files, as python and matlab store matrices in an order transposed to each other.

As a general principle, SplAdder will identify a current project by output directory (set via option -o <dirname>). Inside <dirname> SplAdder will generate an internal structure that is assumed to stay unchanged. This will guarantee that a SplAdder computation can be restarted if interrupted at any point without loosing intermediate results. Further, downstream analyses such as visualizations will use this structure to collect all the information they need about the SplAdder run. So please do not alter the structure in the SplAdder output directory.

The SplAdder Pipeline

SplAdder can be divided into three major parts:

• Augmentation Phase - Annotation augmentation with evidence from provided RNA-Seq alignments.
• Event Detection Phase - Alternative event detection and quantification based on augmented splicing graphs built during the previous phase.
• Result Inspection Phase - Further inspection of the detected and quantified alternative splicing events through visualization and/or differential analysis

Each of these three phases requires the previous phases to be completed. Details about each phase are described on the respective wiki pages linked in the list above.

SplAdder Tutorial

The tutorial pages are small walk-through examples on how to apply SplAdder in some typical use cases. If tutorials built upon each other this is reflected in their numbering. Roman numbers identify independent tutorials whereas letters show an ordering amongst tutorials having the same number.

• 1a - Getting Started
• 1b - Augment Annotation
• 1c - Event Detection