Literature DB >> 21113236

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

Susmita Datta1, Somnath Datta, Seongho Kim, Sutirtha Chakraborty, Ryan S Gill.   

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.

Entities:  

Year:  2010        PMID: 21113236      PMCID: PMC2989618          DOI: 10.4172/jpb.1000138

Source DB:  PubMed          Journal:  J Proteomics Bioinform        ISSN: 0974-276X


  66 in total

1.  Mapping short DNA sequencing reads and calling variants using mapping quality scores.

Authors:  Heng Li; Jue Ruan; Richard Durbin
Journal:  Genome Res       Date:  2008-08-19       Impact factor: 9.043

2.  BayesCall: A model-based base-calling algorithm for high-throughput short-read sequencing.

Authors:  Wei-Chun Kao; Kristian Stevens; Yun S Song
Journal:  Genome Res       Date:  2009-08-06       Impact factor: 9.043

Review 3.  Computational methods for discovering structural variation with next-generation sequencing.

Authors:  Paul Medvedev; Monica Stanciu; Michael Brudno
Journal:  Nat Methods       Date:  2009-11       Impact factor: 28.547

4.  F-Seq: a feature density estimator for high-throughput sequence tags.

Authors:  Alan P Boyle; Justin Guinney; Gregory E Crawford; Terrence S Furey
Journal:  Bioinformatics       Date:  2008-09-10       Impact factor: 6.937

5.  Genome-wide mapping of in vivo protein-DNA interactions.

Authors:  David S Johnson; Ali Mortazavi; Richard M Myers; Barbara Wold
Journal:  Science       Date:  2007-05-31       Impact factor: 47.728

6.  Visualization of genomic data with the Hilbert curve.

Authors:  Simon Anders
Journal:  Bioinformatics       Date:  2009-03-17       Impact factor: 6.937

7.  Comparison of next generation sequencing technologies for transcriptome characterization.

Authors:  P Kerr Wall; Jim Leebens-Mack; André S Chanderbali; Abdelali Barakat; Erik Wolcott; Haiying Liang; Lena Landherr; Lynn P Tomsho; Yi Hu; John E Carlson; Hong Ma; Stephan C Schuster; Douglas E Soltis; Pamela S Soltis; Naomi Altman; Claude W dePamphilis
Journal:  BMC Genomics       Date:  2009-08-01       Impact factor: 3.969

8.  Parameter estimation for robust HMM analysis of ChIP-chip data.

Authors:  Peter Humburg; David Bulger; Glenn Stone
Journal:  BMC Bioinformatics       Date:  2008-08-18       Impact factor: 3.169

9.  Substantial biases in ultra-short read data sets from high-throughput DNA sequencing.

Authors:  Juliane C Dohm; Claudio Lottaz; Tatiana Borodina; Heinz Himmelbauer
Journal:  Nucleic Acids Res       Date:  2008-07-26       Impact factor: 16.971

10.  Design and analysis of ChIP-seq experiments for DNA-binding proteins.

Authors:  Peter V Kharchenko; Michael Y Tolstorukov; Peter J Park
Journal:  Nat Biotechnol       Date:  2008-11-16       Impact factor: 54.908

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  15 in total

1.  DNA methylation screening and analysis.

Authors:  Karilyn E Sant; Muna S Nahar; Dana C Dolinoy
Journal:  Methods Mol Biol       Date:  2012

2.  Development of InDel markers for Brassica rapa based on whole-genome re-sequencing.

Authors:  Bo Liu; Yan Wang; Wen Zhai; Jie Deng; Hui Wang; Yang Cui; Feng Cheng; Xiaowu Wang; Jian Wu
Journal:  Theor Appl Genet       Date:  2012-09-13       Impact factor: 5.699

3.  Technical and biological variance structure in mRNA-Seq data: life in the real world.

Authors:  Ann L Oberg; Brian M Bot; Diane E Grill; Gregory A Poland; Terry M Therneau
Journal:  BMC Genomics       Date:  2012-07-07       Impact factor: 3.969

Review 4.  Base-calling for next-generation sequencing platforms.

Authors:  Christian Ledergerber; Christophe Dessimoz
Journal:  Brief Bioinform       Date:  2011-01-18       Impact factor: 11.622

5.  Characterization and improvement of RNA-Seq precision in quantitative transcript expression profiling.

Authors:  Paweł P Łabaj; Germán G Leparc; Bryan E Linggi; Lye Meng Markillie; H Steven Wiley; David P Kreil
Journal:  Bioinformatics       Date:  2011-07-01       Impact factor: 6.937

6.  Estimation of allele frequency and association mapping using next-generation sequencing data.

Authors:  Su Yeon Kim; Kirk E Lohmueller; Anders Albrechtsen; Yingrui Li; Thorfinn Korneliussen; Geng Tian; Niels Grarup; Tao Jiang; Gitte Andersen; Daniel Witte; Torben Jorgensen; Torben Hansen; Oluf Pedersen; Jun Wang; Rasmus Nielsen
Journal:  BMC Bioinformatics       Date:  2011-06-11       Impact factor: 3.169

7.  UrQt: an efficient software for the Unsupervised Quality trimming of NGS data.

Authors:  Laurent Modolo; Emmanuelle Lerat
Journal:  BMC Bioinformatics       Date:  2015-04-29       Impact factor: 3.169

8.  Genome-wide genetic variation and comparison of fruit-associated traits between kumquat (Citrus japonica) and Clementine mandarin (Citrus clementina).

Authors:  Tian-Jia Liu; Yong-Ping Li; Jing-Jing Zhou; Chun-Gen Hu; Jin-Zhi Zhang
Journal:  Plant Mol Biol       Date:  2018-02-26       Impact factor: 4.076

9.  Bioinformatics of Cancer ncRNA in High Throughput Sequencing: Present State and Challenges.

Authors:  Natasha Andressa Nogueira Jorge; Carlos Gil Ferreira; Fabio Passetti
Journal:  Front Genet       Date:  2012-12-17       Impact factor: 4.599

10.  De novo assembly and transcriptome analysis of two contrary tillering mutants to learn the mechanisms of tillers outgrowth in switchgrass (Panicum virgatum L.).

Authors:  Kaijie Xu; Fengli Sun; Guaiqiang Chai; Yongfeng Wang; Lili Shi; Shudong Liu; Yajun Xi
Journal:  Front Plant Sci       Date:  2015-09-16       Impact factor: 5.753

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