ReviewEnvironmental and molecular mutagenesis2007
Review of the literature examining the correlation among DNA microarray technologies.
Review in Environmental and molecular mutagenesis, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
21 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A novel tissue-specific meta-analysis approach for gene expression predictions, initiated with a mammalian gene expression testis database.BMC genomics · 2010Pooled it
- Research on Key Technologies of Microarray Chips for Detecting Drug-Resistant Genes inMicromachines · 2024Article
- Genotyping Multidrug-Resistant Mycobacterium tuberculosis from Primary Sputum and Decontaminated Sediment with an Integrated Microfluidic Amplification Microarray Test.Journal of clinical microbiology · 2018Article
- How consistent are we? Interlaboratory comparison study in fathead minnows using the model estrogen 17α-ethinylestradiol to develop recommendations for environmental transcriptomics.Environmental toxicology and chemistry · 2017Article
- Perspectives on genetically modified crops and food detection.Journal of food and drug analysis · 2016Review
- Technical guide for applications of gene expression profiling in human health risk assessment of environmental chemicals.Regulatory toxicology and pharmacology : RTP · 2015Article
- Simplified microarray system for simultaneously detecting rifampin, isoniazid, ethambutol, and streptomycin resistance markers in Mycobacterium tuberculosis.Journal of clinical microbiology · 2014Article
- Microarray-based RNA profiling of breast cancer: batch effect removal improves cross-platform consistency.BioMed research international · 2014Article
- Article
- Current status and future directions of gene expression profiling in Parkinson's disease.Neurobiology of disease · 2012Review
- Empirical comparison of cross-platform normalization methods for gene expression data.BMC bioinformatics · 2011Article
- Comparison of lists of genes based on functional profiles.BMC bioinformatics · 2011Article
- Article
- Metabolic network analysis of Pseudomonas aeruginosa during chronic cystic fibrosis lung infection.Journal of bacteriology · 2010Article
- Should we abandon the t-test in the analysis of gene expression microarray data: a comparison of variance modeling strategies.PloS one · 2010Article
- Consistency of predictive signature genes and classifiers generated using different microarray platforms.The pharmacogenomics journal · 2010Article
- Cross-platform analysis of global microRNA expression technologies.BMC genomics · 2010Article
- Comparison of lung cancer cell lines representing four histopathological subtypes with gene expression profiling using quantitative real-time PCR.Cancer cell international · 2010Article
- Ratio adjustment and calibration scheme for gene-wise normalization to enhance microarray inter-study prediction.Bioinformatics (Oxford, England) · 2009Article
- Institutional shared resources and translational cancer research.Journal of translational medicine · 2009Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
DNA microarray technologies are used in a variety of biological disciplines. The diversity of platforms and analytical methods employed has raised concerns over the reliability, reproducibility and correlation of data produced across the different approaches. Initial investigations (years 2000-2003) found discrepancies in the gene expression measures produced by different microarray technologies. Increasing knowledge and control of the factors that result in poor correlation among the technologies has led to much higher levels of correlation among more recent publications (years 2004 to present). Here, we review the studies examining the correlation among microarray technologies. We find that with improvements in the technology (optimization and standardization of methods, including data analysis) and annotation, analysis across platforms yields highly correlated and reproducible results. We suggest several key factors that should be controlled in comparing across technologies, and are good microarray practice in general.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.