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In this review we discuss the latest targeted enrichment methods, and aspects of their utilization along with second generation sequencing for complex genome analysis. In doing so we provide an overview of issues involved in detecting genetic variation, for which targeted enrichment has become a powerful tool. We explain how targeted enrichment for next generation sequencing has made great progress in terms of methodology, ease of use and applicability, but emphasize the remaining challenges such as the lack of even coverage across targeted regions. Costs are also considered versus the alternative of whole genome sequencing which is becoming ever more affordable. We conclude that targeted enrichment is likely to be the most economical option for many years to come in a range of settings.

The use of a priori knowledge in aligning targeted sequencing data is investigated using computational experiments. With conventional aligners such as Bowtie, BWA or MAQ, alignment is performed against the whole genome. Using an alignment method in which the genomic position information from the target capture is incorporated, alignment can be done to just the target region. Investigating the effect of realistic target size, read length, read redundancy, the amount of off-target reads and sequencing error rate, improvements of up to a factor of 8 +/- 0.3 in alignment speed are found using an implementation of the Needleman-Wunsch algorithm which makes use of direct stringcomparison. This results in a total alignment time in target sequencing of around 1 min.