Evidence map›Paper›PMID 19176604›Full record

ArticleRNA (New York, N.Y.)2009

Impact of normalization on miRNA microarray expression profiling.

Sylvain Pradervand, Johann Weber, Jérôme Thomas, Manuel Bueno, Pratyaksha Wirapati, Karine Lefort, G Paolo Dotto, Keith Harshman

Open access · bronzeAbstract readEvaluation Study
In one paragraph

Article in RNA (New York, N.Y.), 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 98 papers.

0numbers the graph read from it
0cells of the map it votes in
98citing papers in PubMed
8.6field-weighted citation impact, top 2% of its field
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

98 citing papers in PubMed, 173 citations in OpenAlex.

  1. Trial
  2. Trial
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. A Post-Processing Algorithm for miRNA Microarray Data.International journal of molecular sciences · 2020
    Article
  13. Article
  14. Article
  15. Article
  16. Review
  17. Article
  18. Article
  19. Article
  20. Article

38 more citing papers are in PubMed but not listed here.

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

8 authors at 2 institutions in 1 country.

Sylvain PradervandLausanne DNA Array Facility, Center for Integrative Genomics, University of Lausanne, CH-1015 Lausanne, Switzerland. Sylvain.Pradervand@unil.ch
Johann Weber
Jérôme Thomas
Manuel Bueno
Pratyaksha Wirapati
Karine Lefort
G Paolo Dotto
Keith Harshman
University of Lausanne · CHSIB Swiss Institute of Bioinformatics · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Profiling miRNA levels in cells with miRNA microarrays is becoming a widely used technique. Although normalization methods for mRNA gene expression arrays are well established, miRNA array normalization has so far not been investigated in detail. In this study we investigate the impact of normalization on data generated with the Agilent miRNA array platform. We have developed a method to select nonchanging miRNAs (invariants) and use them to compute linear regression normalization coefficients or variance stabilizing normalization (VSN) parameters. We compared the invariants normalization to normalization by scaling, quantile, and VSN with default parameters as well as to no normalization using samples with strong differential expression of miRNAs (heart-brain comparison) and samples where only a few miRNAs are affected (by p53 overexpression in squamous carcinoma cells versus control). All normalization methods performed better than no normalization. Normalization procedures based on the set of invariants and quantile were the most robust over all experimental conditions tested. Our method of invariant selection and normalization is not limited to Agilent miRNA arrays and can be applied to other data sets including those from one color miRNA microarray platforms, focused gene expression arrays, and gene expression analysis using quantitative PCR.

Indexed as

MicroRNAsGene Expression ProfilingHumansLinear ModelsMicroarray AnalysisSensitivity and SpecificityMicroRNAs

Identifiers

PMID19176604
PMCPMC2657010
OpenAlexW2118473681

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.