An improved maximum likelihood formulation for accurate genome assembly

We present improvements to the recently proposed maximum likelihood method for genome assembly. We formulate the problem as one of direct convex optimization, and achieve the following improvements: Our method does not require identical read lengths and can deal with reads of varying lengths. We eliminate the requirement to a priori know a stringent estimate of the length of the genome or the need to use further expectation minimization to predict the most likely length. Instead, we explicitly incorporate the uncertainty in the length estimate by a range parameter without affecting the convexity required for the optimization. Results indicate that our method can generate accurate estimates of repeat counts and produces fewer and much longer contigs. These results mark a further advancement of maximum likelihood genome assembly and the potential of this approach in building future genome assemblers.