Abstract
We introduce a new method for filtering noisy 3C interactions that selects subsets of interactions that obey metric constraints of various strictness. We demonstrate that, although the problem is computationally hard, near-optimal results are often attainable in practice using well-designed heuristics and approximation algorithms. Further, we show that, compared with a standard technique, this metric filtering approach leads to (a) subgraphs with higher total statistical significance, (b) lower embedding error, (c) lower sensitivity to initial conditions of the embedding algorithm, and (d) structures with better agreement with light microscopy measurements.
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Baù, D., et al.: The three-dimensional folding of the α-globin gene domain reveals formation of chromatin globules. Nat. Struct. & Mol. Biol. 18(1), 107–114 (2010)
Dekker, J., et al.: Capturing chromosome conformation. Science 295(5558), 1306–1311 (2002)
Duan, Z., et al.: A three-dimensional model of the yeast genome. Nature 465(7296), 363–367 (2010)
Fudenberg, G., et al.: High-order chromatin architecture determines the landscape of chromosomal alterations in cancer. Nat. Biotechnol. 29(12), 1109–1113 (2011), http://www.ncbi.nlm.nih.gov/pubmed/22101486 , doi:10.1038/nbt.2049
Gomes, C., Williams, R.: Approximation algorithms. In: Burke, E.K., Kendall, G. (eds.) Search Methodologies: Introductory Tutorials in Optimization and Decision Support Techniques, ch. 18. Springer (2005)
Hochbaum, D.S. (ed.): Approximation algorithms for NP-hard problems. PWS Publishing Co, Boston (1997)
Kalhor, R., et al.: Genome architectures revealed by tethered chromosome conformation capture and population-based modeling. Nat. Biotechnol. 30(1), 90–98 (2012)
Lieberman-Aiden, E., et al.: Comprehensive mapping of long-range interactions reveals folding principles of the human genome. Science 326(5950), 289–293 (2009)
Marti-Renom, M.A., Mirny, L.A.: Bridging the resolution gap in structural modeling of 3D genome organization. PLoS Comput. Biol. 7(7), 1002125 (2011)
Niedermeier, R., Rossmanith, P.: An efficient fixed-parameter algorithm for 3-hitting set. Journal of Discrete Algorithms 1(1), 89–102 (2003)
Rousseau, M., et al.: Three-dimensional modeling of chromatin structure from interaction frequency data using Markov chain Monte Carlo sampling. BMC Bioinformatics 12(1), 414 (2011)
Saxe, J.: Embeddability of weighted graphs in k-space is strongly NP-hard. In: 17th Allerton Conference in Communications, Control and Computing, pp. 480–489 (1979)
Sexton, T., et al.: Three-dimensional folding and functional organization principles of the Drosophila genome. Cell 148(3), 458–472 (2012)
Tanizawa, H., et al.: Mapping of long-range associations throughout the fission yeast genome reveals global genome organization linked to transcriptional regulation. Nuc. Acids Res. 38(22), 8164–8177 (2010)
Theobald, D.L., Wuttke, D.S.: THESEUS: maximum likelihood superpositioning and analysis of macromolecular structures. Bioinformatics 22(17), 2171–2172 (2006)
Therizols, P., et al.: Chromosome arm length and nuclear constraints determine the dynamic relationship of yeast subtelomeres. Proc. Natl. Acad. Sci. USA 107(5), 2025–2030 (2010)
Umbarger, M.A., et al.: The three-dimensional architecture of a bacterial genome and its alteration by genetic perturbation. Mol. Cell 44(2), 252–264 (2011)
Yaffe, E., Tanay, A.: Probabilistic modeling of Hi-C contact maps eliminates systematic biases to characterize global chromosomal architecture. Nature Genetics 43(11), 1059–1065 (2011)
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Duggal, G. et al. (2012). Resolving Spatial Inconsistencies in Chromosome Conformation Data. In: Raphael, B., Tang, J. (eds) Algorithms in Bioinformatics. WABI 2012. Lecture Notes in Computer Science(), vol 7534. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33122-0_23
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DOI: https://doi.org/10.1007/978-3-642-33122-0_23
Publisher Name: Springer, Berlin, Heidelberg
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