Microarrays in brain research: the good, the bad and the ugly.
Making sense of microarray data is a complex process, in which the interpretation of findings will depend on the overall experimental design and judgement of the investigator performing the analysis. As a result, differences in tissue harvesting, microarray types, sample labelling and data analysis procedures make post hoc sharing of microarray data a great challenge. To ensure rapid and meaningful data exchange, we need to create some order out of the existing chaos. In these ground-breaking microarray standardization and data sharing efforts, NIH agencies should take a leading role
Mirnics
K
K
Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA. karoly+@pitt.edu
D000818:Animals; D016208:Databases, Factual / Q000592:standards* / Q000639:trends*; D001330:Electronic Data Processing / Q000592:standards / Q000639:trends; D015870:Gene Expression / Q000502:physiology*; D006801:Humans; D009316:National Institutes of Health (U.S.) / Q000592:standards / Q000639:trends; D009488:Neurosciences / Q000379:methods* / Q000639:trends*; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods / Q000592:standards* / Q000639:trends*; D015203:Reproducibility of Results; D012107:Research Design / Q000592:standards / Q000639:trends; D014481:United States