title: Impact of experimental noise and annotation imprecision on data quality in microarray experiments.
abstract: Data quality is intrinsically influenced by design, technical, and analytical parameters. Quality parameters have not yet been well defined for gene expression analysis by microarrays, though ad interim, following recommended good experimental practice guidelines should ensure generation of reliable and reproducible data. Here we summarize essential practical recommendations for experimental design, technical considerations, feature annotation issues, and standardization efforts.
authors: Genomics, Biomarker Development, Spheromics, Kontiolahti, Joensuu, Finland. Andreas.Scherer@agrf.org.au
authors: Andreas
authors: A
authors: Scherer
authors: Manhong
authors: M
authors: Dai
authors: Fan
authors: F
authors: Meng
mesh_terms: D016022:Case-Control Studies; D015342:DNA Probes / Q000235:genetics; D003627:Data Interpretation, Statistical; D005091:Exons; D020869:Gene Expression Profiling / Q000592:standards* / Q000706:statistics & numerical data; D005787:Gene Frequency; D015894:Genome, Human; D006801:Humans; D058977:Molecular Sequence Annotation / Q000592:standards; D015588:Observer Variation; D020411:Oligonucleotide Array Sequence Analysis / Q000592:standards* / Q000706:statistics & numerical data; D020641:Polymorphism, Single Nucleotide; D011786:Quality Control; D012015:Reference Standards; D015203:Reproducibility of Results; D012107:Research Design; D059629:Signal-To-Noise Ratio; D013048:Specimen Handling / Q000592:standards
chemical_list: D015342:DNA Probes