SUMMARY: Here we present Sequence Variant Analyzer (SVA), a software tool that assigns a predicted biological function to variants identified in next-generation sequencing studies and provides a browser to visualize the variants in their genomic contexts. SVA also provides for flexible interaction with software implementing variant association tests allowing users to consider both the bioinformatic annotation of identified variants and the strength of their associations with studied traits. We illustrate the annotation features of SVA using two simple examples of sequenced genomes that harbor Mendelian mutations. AVAILABILITY AND IMPLEMENTATION: Freely available on the web at http://www.svaproject.org.

For many years the attempts to identify functional elements in genomic sequences through motif over- representation have been problematic, as every procedure to isolate such motifs resulted in a very large number of candidates with highly significant p-values. In this paper we postulate that most of these elements originate in ancient transpositional activity, with copies becoming so broken over time that they cannot be recognized as such any more. We have written a software tool which efficiently locates possible ancient repeats and, while the nature of much of our findings in real genomic sequences have yet to be confirmed by further biological analysis, our test results on well understood data sets have been encouraging.