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Anton Valouev

Publications and source records attributed to Anton Valouev.

3 recordsLinked to original sources

An algorithm for assembly of ordered restriction maps from single DNA molecules.

The restriction mapping of a massive number of individual DNA molecules by optical mapping enables assembly of physical maps spanning mammalian and plant genomes; however, not through computational means permitting completely de novo assembly. Existing algorithms are not practical for genomes larger than lower eukaryotes due to their high time and space complexity. In many ways, sequence assembly parallels map assembly, so that the overlap-layout-consensus strategy, recently shown effective in assembling very large genomes in feasible time, sheds new light on solving map construction issues associated with single molecule substrates. Accordingly, we report an adaptation of this approach as the formal basis for de novo optical map assembly and demonstrate its computational feasibility for assembly of very large genomes. As such, we discuss assembly results for a series of genomes: human, plant, lower eukaryote and bacterial. Unlike sequence assembly, the optical map assembly problem is actually more complex because restriction maps from single molecules are constructed, manifesting errors stemming from: missing cuts, false cuts, and high variance of estimated fragment sizes; chimeric maps resulting from artifactually merged molecules; and true overlap scores that are "in the noise" or "slightly above the noise." We address these problems, fundamental to many single molecule measurements, by an effective error correction method using global overlap information to eliminate spurious overlaps and chimeric maps that are otherwise difficult to identify.

Algorithms↗

Refinement of optical map assemblies.

MOTIVATION: Genomic mutations and variations provide insightful information about the functionality of sequence elements and their association with human diseases. Traditionally, variations are identified through analysis of short DNA sequences, usually shorter than 1000 bp per fragment. Optical maps provide both faster and more cost-efficient means for detecting such differences, because a single map can span over 1 million bp. Optical maps are assembled to cover the whole genome, and the accuracy of assembly is critical. RESULTS: We present a computationally efficient model-based method for improving quality of such assemblies. Our method provides very high accuracy even with moderate coverage (<20 x). We utilize a hidden Markov model to represent the consensus map and use the expectation-Maximization algorithm to drive the refinement process. We also provide quality scores to assess the quality of the finished map. AVAILABILITY: Code is available from www.cmb.usc.edu/people/valouev/

Algorithms↗

Alignment of optical maps.

We introduce a new scoring method for calculation of alignments of optical maps. Missing cuts, false cuts, and sizing errors present in optical maps are addressed by our alignment score through calculation of corresponding likelihoods. The size error model is derived through the application of Central Limit Theorem and validated by residual plots collected from real data. Missing cuts and false cuts are modeled as Bernoulli and Poisson events, respectively, as suggested by previous studies. Likelihoods are used to derive an alignment score through calculation of likelihood ratios for a certain hypothesis test. This allows us to achieve maximal descriminative power for the alignment score. Our scoring method is naturally embedded within a well known DP framework for finding optimal alignments.

Algorithms↗