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. © 2012 Springer-Verlag.
CITATION STYLE
Duggal, G., Patro, R., Sefer, E., Wang, H., Filippova, D., Khuller, S., & Kingsford, C. (2012). Resolving spatial inconsistencies in chromosome conformation data. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7534 LNBI, pp. 288–300). https://doi.org/10.1007/978-3-642-33122-0_23
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