  In the past several years, the problem of genome assembly has received
considerable attention from both biologists and computer scientists. An
important component of current assembly methods is the scaffolding process.
This process involves building ordered and oriented linear collections of
contigs (continuous overlapping sequence reads) called scaffolds and relies on
the use of mate pair data. A mate pair is a set of two reads that are sequenced
from the ends of a single fragment of DNA, and therefore have opposite mutual
orientations. When two reads of a mate-pair are placed into two different
contigs, one can infer the mutual orientation of these contigs. While several
orientation algorithms exist as part of assembly programs, all encounter
challenges while solving the orientation problem due to errors from
mis-assemblies in contigs or errors in read placements. In this paper we
present an algorithm based on hierarchical clustering that independently solves
the orientation problem and is robust to errors. We show that our algorithm can
correctly solve the orientation problem for both faux (generated) assembly data
and real assembly data for {\em R. sphaeroides bacteria}. We demonstrate that
our algorithm is stable to both changes in the initial orientations as well as
noise in the data, making it advantageous compared to traditional approaches.
