Evidence map›Paper›PMID 21113236›Full record

ArticleJournal of proteomics & bioinformatics2010

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

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

Abstract read
In one paragraph

Article in Journal of proteomics & bioinformatics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed.

  1. Article
  2. Article
  3. Identifying the genome-wide genetic variation between precocious trifoliate orange and its wild type and developing new markers for genetics research.DNA research : an international journal for rapid publication of reports on genes and genomes · 2016
    Article
  4. Article
  5. Article
  6. Article
  7. Experience of targeted Usher exome sequencing as a clinical test.Molecular genetics & genomic medicine · 2014
    Article
  8. Article
  9. Development of InDel markers for Brassica rapa based on whole-genome re-sequencing.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2013
    Article
  10. Article
  11. Article
  12. DNA methylation screening and analysis.Methods in molecular biology (Clifton, N.J.) · 2012
    Article
  13. Review
  14. Article
  15. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Susmita DattaDepartment of Bioinformatics and Biostatistics, University of Louisville, Louisville, KY 40202, USA.
Somnath Datta
Seongho Kim
Sutirtha Chakraborty
Ryan S Gill

Funding

Strategic Vision & Impact on Environmental HealthP30ES014443 · NIEHS · UNIVERSITY OF LOUISVILLE · PI PROUGH, RUSSELL ALLEN · 2007 to 2010
$4.4M
Development of Statistical Methods for Analyzing Proteomic Cancer DataR15CA133844 · NCI · UNIVERSITY OF LOUISVILLE · PI DATTA, SUSMITA · 2009 to 2009
$222k
NCI NIH HHS R15 CA133844NIEHS NIH HHS P30 ES014443
6 · The paper itself

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.

Identifiers

PMID21113236
PMCPMC2989618

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.