Statistical Analyses of Next Generation Sequence Data: A Partial Overview

  • Datta S
  • Datta S
  • Kim S
  • et al.
N/ACitations
Citations of this article
179Readers
Mendeley users who have this article in their library.

Abstract

Next generation sequencing has revolutionized the status of biological research. For a long time, the gold standard of DNA sequencing was considered to be the Sanger method. However, in 2005, commercial launching of next generation sequencing has made it possible to generate massively parallel and high resolution DNA sequence data. Its usefulness in various genomic applications such as genome-wide detection of SNPs, DNA methylation profiling, mRNA expression profiling, whole-genome re-sequencing and so on are now well recognized. There are several platforms for generating next generation sequencing (NGS) data which we briefly discuss in this mini overview. With new technologies come new challenges for the data analysts. This mini review attempts to present a collection of selected topics in the current development of statistical methods dealing with these novel data types. We believe that knowing the advances and bottlenecks of this technology will help the researchers to benchmark the analytical tools dealing with these data and will pave the path for its proper application into clinical diagnostics

Cite

CITATION STYLE

APA

Datta, S., Datta, S., Kim, S., Chakraborty, S., & Gill, R. S. (2010). Statistical Analyses of Next Generation Sequence Data: A Partial Overview. Journal of Proteomics & Bioinformatics, 03(06), 183–190. https://doi.org/10.4172/jpb.1000138

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free