Abstract
We propose a formal model and an algorithm for detecting inversion breakpoints without a reference genome, directly from raw NGS data. This model is characterized by a fixed size topological pattern in the de Bruijn Graph. We describe precisely the possible sources of false positives and false negatives and we additionally propose a sequence-based filter giving a good trade-off between precision and recall of the method. We implemented these ideas in a prototype called TakeABreak. Applied on simulated inversions in genomes of various complexity (from E. coli to a human chromosome dataset), TakeABreak provided promising results with a low memory footprint and a small computational time.
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Lemaitre, C., Ciortuz, L., Peterlongo, P. (2014). Mapping-Free and Assembly-Free Discovery of Inversion Breakpoints from Raw NGS Reads. In: Dediu, AH., MartÃn-Vide, C., Truthe, B. (eds) Algorithms for Computational Biology. AlCoB 2014. Lecture Notes in Computer Science(), vol 8542. Springer, Cham. https://doi.org/10.1007/978-3-319-07953-0_10
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DOI: https://doi.org/10.1007/978-3-319-07953-0_10
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