Optimizing the BAC-End Strategy for Sequencing the Human Genome
Ron Shamir (joint with R. M. Karp),
Sep 7, 1998
The rapid increase in human genome sequencing effort and the emergence of
several alternative strategies to large-scale sequencing raise the need for
a thorough comparison of such strategies.
This paper provides a mathematical analysis of the BAC-end strategy,
showing how to obtain an optimal choice of parameters.
The analysis makes very mild assumptions. In particular,
it accommodates variable clone length and inhomogeneity of
the distribution of clone positions. The analysis implies that the BAC-end
strategy is very close to optimal in terms of cost, under a wide range
of experimental scenarios.
We'll probably dwell more on the context and the Human Genome Race
story surrounding the topic than on the math which is quite simple.