Next-generation high throughput sequencing technologies have opened up a wide range of new genome research opportunities. High throughput sequencing technologies produces a massive amount of short reads data in a single run. The large dataset produced by short read sequencing technologies are highly error-prone as compared to traditional Sanger sequencing approaches. These errors are critical and removing them is challenging. Therefore, there are peremptory demands for statistical tools for bioinformatics to analyze such large amounts of data. In this paper, we present review of and measuring parameters associated with genome sequence short read errors correction tools and algorithms. We further present comprehensive detail of datasets and results obtained with defined parameters. The reviews present the current state of the art and future directions in the area as well.
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