  Motivation: Intimately tied to assembly quality is the complexity of the de
Bruijn graph built by the assembler. Thus, there have been many paradigms
developed to decrease the complexity of the de Bruijn graph. One obvious
combinatorial paradigm for this is to allow the value of $k$ to vary; having a
larger value of $k$ where the graph is more complex and a smaller value of $k$
where the graph would likely contain fewer spurious edges and vertices. One
open problem that affects the practicality of this method is how to predict the
value of $k$ prior to building the de Bruijn graph. We show that optimal values
of $k$ can be predicted prior to assembly by using the information contained in
a phylogenetically-close genome and therefore, help make the use of multiple
values of $k$ practical for genome assembly.
  Results: We present HyDA-Vista, which is a genome assembler that uses
homology information to choose a value of $k$ for each read prior to the de
Bruijn graph construction. The chosen $k$ is optimal if there are no sequencing
errors and the coverage is sufficient. Fundamental to our method is the
construction of the {\em maximal sequence landscape}, which is a data structure
that stores for each position in the input string, the largest repeated
substring containing that position. In particular, we show the maximal sequence
landscape can be constructed in $O(n + n \log n)$-time and $O(n)$-space.
HyDA-Vista first constructs the maximal sequence landscape for a homologous
genome. The reads are then aligned to this reference genome, and values of $k$
are assigned to each read using the maximal sequence landscape and the
alignments. Eventually, all the reads are assembled by an iterative de Bruijn
graph construction method. Our results and comparison to other assemblers
demonstrate that HyDA-Vista achieves the best assembly of {\em E. coli} before
repeat resolution or scaffolding.
