Large-scale population and disease association studies have shown the importance as well as the difficulty of detecting structural variants (SVs) in genomic and also transcriptomic sequencing data. Although being very fast and precise, current read mapping tools usually fail to map sequencing reads that cross SV breakpoints or exon-exon boundaries. These events cause one or even multiple splits in the read-to-reference alignment, with parts of the read mapping to various locations on the reference sequence.
We present GUSTAF, a sound generic multi-split detection method. GUSTAF uses SeqAn’s exact local aligner STELLAR to find partial read alignments. Compatible partial alignments are identified, and a split-read graph storing all compatibility information is constructed for each read. Vertices in the graph represent partial alignments, edges represent possible split positions. Using an exact dynamic programming approach, we refine the alignments around possible split positions to determine precise breakpoint locations at single-nucleotide level. We use a DAG shortest path algorithm to determine the best combination of refined alignments, and report those breakpoints supported by multiple reads.
Usage: STELLAR is not a read mapper, and hence, GUSTAF is not designed to replace any read mapper pipeline with SV detection on top. We recommend doing read mapping with your favourite read mapper and then run STELLAR and GUSTAF, seperately, on the remaining unmappable reads.
Please take a look at the README file for usage instructions.
- Download the binaries
- View the source code and README on GitHub
- Benchmark Data (v1.0) – The data used for obtaining the results of the 2014 paper.
- Trappe, K., Emde, A.-K., Ehrlich, H.-C., Reinert, K. (2014). Gustaf: Detecting and correctly classifiying SVs in the NGS twilight zone. Bioinformatics.
- Trappe, K. (2012). Multi-Split Mapping of NGS Reads for Variant Detection. Master’s thesis, Freie Universitaet Berlin.
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