[en] Cancer ; structural variation ; computational
[en] Identifying large-scale structural variation in cancer genomes continues to be a challenge to researchers. Current methods rely on genome alignments based on a reference that can be a poor fit to highly variant and complex tumor genomes. To address this challenge we developed a method that uses available breakpoint information to generate models of structural variations. We use these models as references to align previously unmapped and discordant reads from a genome. By using these models to align unmapped reads, we show that our method can help to identify large-scale variations that have been previously missed.
Luxembourg Centre for Systems Biomedicine (LCSB): Bioinformatics Core (R. Schneider Group) ; University of Luxembourg: High Performance Computing - ULHPC ; Luxembourg Centre for Systems Biomedicine (LCSB): Computational Biology (Del Sol Group)
[University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
