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Detecting Superbubbles in Assembly Graphs
We introduce a new concept of a subgraph class called a superbubble for
analyzing assembly graphs, and propose an efficient algorithm for detecting it.
Most assembly algorithms utilize assembly graphs like the de Bruijn graph or
the overlap graph constructed from reads. From these graphs, many assembly
algorithms first detect simple local graph structures (motifs), such as tips
and bubbles, mainly to find sequencing errors. These motifs are easy to detect,
but they are sometimes too simple to deal with more complex errors. The
superbubble is an extension of the bubble, which is also important for
analyzing assembly graphs. Though superbubbles are much more complex than
ordinary bubbles, we show that they can be efficiently enumerated. We propose
an average-case linear time algorithm (i.e., O(n+m) for a graph with n vertices
and m edges) for graphs with a reasonable model, though the worst-case time
complexity of our algorithm is quadratic (i.e., O(n(n+m))). Moreover, the
algorithm is practically very fast: Our experiments show that our algorithm
runs in reasonable time with a single CPU core even against a very large graph
of a whole human genome.Comment: Peer-reviewed and presented as part of the 13th Workshop on
Algorithms in Bioinformatics (WABI2013
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