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PMID: 21113236 Published · ppublish English Journal Article

Statistical Analyses of Next Generation Sequence Data: A Partial Overview.

Journal of proteomics & bioinformatics ·Vol. 3 ·No. 6 ·2010-06-01 ·Pages 183-190

Datta S, Datta S, Kim S, Chakraborty S, Gill RS

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.

Authors & Affiliations
5 authors, click to expand affiliations / ORCID
Datta Susmita
Department of Bioinformatics and Biostatistics, University of Louisville, Louisville, KY 40202, USA.
Datta Somnath
Kim Seongho
Chakraborty Sutirtha
Gill Ryan S
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Article Info
Journal
Journal of proteomics & bioinformatics
Abbr.
J Proteomics Bioinform
ISSN
0974-276X
DOI
10.4172/jpb.1000138
Published
2010-06-01
Pages
183-190
Language
English
Region
United States
NLM ID
101479045
PMCID
PMC2989618
Grants
NIEHS NIH HHS · P30 ES014443 · United States
NCI NIH HHS · R15 CA133844 · United States
NCI NIH HHS · R15 CA133844-01A2 · United States
External Links
PubMed source DOI: 10.4172/jpb.1000138 PMC Full Text
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