While next generation sequencers all target high-throughput sequencing, they have unique error characteristics that result from the sequencing methodology. Correcting sequence errors by taking advantage of deep coverage sampling and low error rates is an important problem in next-gen sequence analysis. Identifying and fixing errors thereby improving data quality can have significant impact on applications. For instance, error correction prior to assembly can have significant impact on contig lengths and accuracy. This talk will provide an overview of our work in error correction algorithms.