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Mapping-Free and Assembly-Free Discovery of Inversion Breakpoints from Raw NGS Reads

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Algorithms for Computational Biology (AlCoB 2014)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 8542))

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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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  1. Alkan, C., Coe, B.P., Eichler, E.E.: Genome structural variation discovery and genotyping. Nat Rev. Genet. 12, 363–376 (2011)

    Article  Google Scholar 

  2. Chikhi, R., Rizk, G.: Space-efficient and exact de bruijn graph representation based on a bloom filter. Algorithms for Molecular Biology 8, 22 (2013)

    Article  Google Scholar 

  3. Drezen, E., et al.: The Genome Assembly and Analysis Tool Box, (Manuscript in Prep. 2014)

  4. Iqbal, Z., Caccamo, M., Turner, I., Flicek, P., McVean, G.: De novo assembly and genotyping of variants using colored de bruijn graphs. Nature Genetics 44, 226–232 (2012)

    Article  Google Scholar 

  5. Lemaitre, C., et al.: MindTheGap Software, (Manuscript in Prep. 2014)

  6. Li, Y., Zheng, H., Luo, R., Wu, H., Zhu, H., Li, R., et al.: Structural variation in two human genomes mapped at single-nucleotide resolution by whole genome de novo assembly. Nat. Biotechnol. 29, 723–730 (2011)

    Article  Google Scholar 

  7. Medvedev, P., Stanciu, M., Brudno, M.: Computational methods for discovering structural variation with next-generation sequencing. Nat Methods 6, S13–S20 (2009)

    Google Scholar 

  8. Mills, R.E., Walter, K., Stewart, C., Handsaker, R.E.: 1000 Genomes Project: Mapping copy number variation by population-scale genome sequencing. Nature 470, 59–65 (2011)

    Article  Google Scholar 

  9. Nordström, K.J.V., Albani, M.C., James, G.V., et al.: Mutation identification by direct comparison of whole-genome sequencing data from mutant and wild-type individuals using k-mers. Nature Biotechnology 31, 325–330 (2013)

    Article  Google Scholar 

  10. Peterlongo, P., Schnel, N., Pisanti, N., Sagot, M.-F., Lacroix, V.: Identifying sNPs without a reference genome by comparing raw reads. In: Chavez, E., Lonardi, S. (eds.) SPIRE 2010. LNCS, vol. 6393, pp. 147–158. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  11. Sacomoto, G.A., Kielbassa, J., Chikhi, R., Uricaru, R., et al.: Kissplice: de-novo calling alternative splicing events from rna-seq data. BMC Bioinformatics 13, S5 (2012)

    Google Scholar 

  12. Salikhov, K., Sacomoto, G., Kucherov, G.: Using Cascading Bloom Filters to Improve the Memory Usage for de Brujin Graphs. In: Darling, A., Stoye, J. (eds.) WABI 2013. LNCS, vol. 8126, pp. 364–376. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  13. Uricaru, R., et al.: discoSnp Software, (Manuscript in Prep. 2014)

  14. Zerbino, D.R., Birney, E.: Velvet: algorithms for de novo short read assembly using de bruijn graphs. Genome Research 18, 821–829 (2008)

    Article  Google Scholar 

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© 2014 Springer International Publishing Switzerland

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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., Martín-Vide, C., Truthe, B. (eds) Algorithms for Computational Biology. AlCoB 2014. Lecture Notes in Computer Science(), vol 8542. Springer, Cham.

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-07952-3

  • Online ISBN: 978-3-319-07953-0

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