Chapter

Algorithms in Bioinformatics

Volume 7534 of the series Lecture Notes in Computer Science pp 288-300

Resolving Spatial Inconsistencies in Chromosome Conformation Data

  • Geet DuggalAffiliated withCarnegie Mellon UniversityDepartment of Computer Science, University of Maryland
  • , Rob PatroAffiliated withCarnegie Mellon UniversityDepartment of Computer Science, University of Maryland
  • , Emre SeferAffiliated withCarnegie Mellon UniversityDepartment of Computer Science, University of Maryland
  • , Hao WangAffiliated withCarnegie Mellon UniversityDepartment of Electrical and Computer Engineering, University of Maryland
  • , Darya FilippovaAffiliated withCarnegie Mellon UniversityDepartment of Computer Science, University of Maryland
  • , Samir KhullerAffiliated withCarnegie Mellon UniversityDepartment of Computer Science, University of Maryland
  • , Carl KingsfordAffiliated withCarnegie Mellon UniversityDepartment of Computer Science, University of Maryland

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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.

Keywords

metric subgraph chromosome conformation