Evidence map›Paper›PMID 16272462›Full record

ArticleNucleic acids research2005

Protocols for the assurance of microarray data quality and process control.

L D Burgoon, J E Eckel-Passow, C Gennings, D R Boverhof, J W Burt, C J Fong, T R Zacharewski

Abstract read
In one paragraph

Article in Nucleic acids research, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

  1. Article
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  14. Toxicogenomic biomarkers for liver toxicity.Journal of toxicologic pathology · 2009
    Article
  15. Quality assessment of microarray data in a multicenter study.Diagnostic molecular pathology : the American journal of surgical pathology, part B · 2009
    Article
  16. MOF: an R function to detect outlier microarray.Genomics, proteomics & bioinformatics · 2008
    Article
  17. Article
  18. Article
  19. Article
  20. 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

7 authors.

L D BurgoonDepartment of Pharmacology and Toxicology, Michigan State University, East Lansing, MI 48824-1319, USA.
J E Eckel-Passow
C Gennings
D R Boverhof
J W Burt
C J Fong
T R Zacharewski

Funding

VOLATILE ORGANIC CONTAMINANTS--QUANTIFYING THEIR MOVEMENT IN THE UNSATURATED ZONEP42ES004911 · NIEHS · MICHIGAN STATE UNIVERSITY · PI Timothy R. Zacharewski · 1989 to 2026
$64.9M
MULTIDISCIPLINARY TRAINING IN ENVIRONMENTAL TOXICOLOGYT32ES007255 · NIEHS · MICHIGAN STATE UNIVERSITY · PI JOHN J LAPRES · 1989 to 2026
$9.3M
Mayo Cancer Genetic Epidemiology Training ProgramR25CA092049 · NCI · MAYO CLINIC ROCHESTER · PI PETERSEN, GLORIA M., VACHON, CELINE M · 2001 to 2018
$5.3M
Integration of Mixtures Toxicology, Toxicogenomics, and StatisticsT32ES007334 · NIEHS · VIRGINIA COMMONWEALTH UNIVERSITY · PI WHEELER, DAVID CHARLES · 2002 to 2018
$2.5M
Ah Receptor-Mediated Ligand ToxicityR01ES012245 · NIEHS · MICHIGAN STATE UNIVERSITY · PI ZACHAREWSKI, TIMOTHY R · 2003 to 2005
$1.1M
Comprehensive Assessment of Endocrine Active MixturesR01ES011271 · NIEHS · MICHIGAN STATE UNIVERSITY · PI ZACHAREWSKI, TIMOTHY R · 2001 to 2003
$990k
NCI NIH HHS R25 CA092049NCI NIH HHS R25 CA92049NIEHS NIH HHS ES11271NIEHS NIH HHS ES12245NIEHS NIH HHS P42 ES004911NIEHS NIH HHS P42 ES04911NIEHS NIH HHS R01 ES011271NIEHS NIH HHS R01 ES012245NIEHS NIH HHS T32 ES007255NIEHS NIH HHS T32 ES007334NIEHS NIH HHS T32 ES07255
6 · The paper itself

Abstract

Microarrays represent a powerful technology that provides the ability to simultaneously measure the expression of thousands of genes. However, it is a multi-step process with numerous potential sources of variation that can compromise data analysis and interpretation if left uncontrolled, necessitating the development of quality control protocols to ensure assay consistency and high-quality data. In response to emerging standards, such as the minimum information about a microarray experiment standard, tools are required to ascertain the quality and reproducibility of results within and across studies. To this end, an intralaboratory quality control protocol for two color, spotted microarrays was developed using cDNA microarrays from in vivo and in vitro dose-response and time-course studies. The protocol combines: (i) diagnostic plots monitoring the degree of feature saturation, global feature and background intensities, and feature misalignments with (ii) plots monitoring the intensity distributions within arrays with (iii) a support vector machine (SVM) model. The protocol is applicable to any laboratory with sufficient datasets to establish historical high- and low-quality data.

Indexed as

Artificial IntelligenceColorGene Expression ProfilingKineticsOligonucleotide Array Sequence AnalysisQuality ControlRegression AnalysisReproducibility of Results

Identifiers

PMID16272462
PMCPMC1278948

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.