Jan 23, 2016

OPTIMA: sensitive and accurate whole-genome alignment of error-prone genomic maps by combinatorial indexing and technology-agnostic statistical analysis

GigaScience
Davide VerzottoNiranjan Nagarajan

Abstract

Resolution of complex repeat structures and rearrangements in the assembly and analysis of large eukaryotic genomes is often aided by a combination of high-throughput sequencing and genome-mapping technologies (for example, optical restriction mapping). In particular, mapping technologies can generate sparse maps of large DNA fragments (150 kilo base pairs (kbp) to 2 Mbp) and thus provide a unique source of information for disambiguating complex rearrangements in cancer genomes. Despite their utility, combining high-throughput sequencing and mapping technologies has been challenging because of the lack of efficient and sensitive map-alignment algorithms for robustly aligning error-prone maps to sequences. We introduce a novel seed-and-extend glocal (short for global-local) alignment method, OPTIMA (and a sliding-window extension for overlap alignment, OPTIMA-Overlap), which is the first to create indexes for continuous-valued mapping data while accounting for mapping errors. We also present a novel statistical model, agnostic with respect to technology-dependent error rates, for conservatively evaluating the significance of alignments without relying on expensive permutation-based tests. We show that OPTIMA and OPTIMA-Overlap o...Continue Reading

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References

Mentioned in this Paper

In Silico
Laboratory Procedures
Genome
Evaluation
Genome Mapping
Genomics
Sequencing
Generalized
Structure
probe gene fragment

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