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Microarray standard data set and figures of merit for comparing data processing methods and experiment designs.

机译:微阵列标准数据集和性能指标,用于比较数据处理方法和实验设计。

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Motivation: There is a very large and growing level of effort toward improving the platforms, experiment designs, and data analysis methods for microarray expression profiling. Along with a growing richness in the approaches there is a growing confusion among most scientists as to how to make objective comparisons and choices between them for different applications. There is a need for a standard framework for the microarray community to compare and improve analytical and statistical methods. Results: We report on a microarray data set comprising 204 in-situ synthesized oligonucleotide arrays, each hybridized with two-color cDNA samples derived from 20 different human tissues and cell lines. Design of the approximately 24 000 60mer oligonucleotides that report approximately 2500 known genes on the arrays, and design of the hybridization experiments, were carried out in a way that supports the performance assessment of alternative data processing approaches and of alternative experiment and array designs. We also propose standard figures of merit for success in detecting individual differential expression changes or expression levels, and for detecting similarities and differences in expression patterns across genes and experiments. We expect this data set and the proposed figures of merit will provide a standard framework for much of the microarray community to compare and improve many analytical and statistical methods relevant to microarray data analysis, including image processing, normalization, error modeling, combining of multiple reporters per gene, use of replicate experiments, and sample referencing schemes in measurements based on expression change. Availability/Supplementary information: Expression data and supplementary information are available at http://www.rii.com/publications/2003/HE_SDS.htm Contact: yudong_he@merck.com
机译:动机:在改进用于微阵列表达谱分析的平台,实验设计和数据分析方法方面,有大量且不断增长的努力。随着方法的日益丰富,大多数科学家对如何针对不同的应用进行客观的比较和选择感到困惑。需要用于微阵列社区的标准框架,以比较和改进分析和统计方法。结果:我们报告了一个微阵列数据集,该数据集包含204个原位合成的寡核苷酸阵列,每个阵列均与源自20种不同人类组织和细胞系的双色cDNA样品杂交。设计了报告阵列上大约2500个已知基因的大约24000个60mer寡核苷酸,并设计了杂交实验,以支持对替代数据处理方法以及替代实验和阵列设计进行性能评估。我们还提出了用于成功检测个体差异表达变化或表达水平以及检测基因和实验中表达模式的相似性和差异性的标准品质因数。我们希望该数据集和拟议的品质因数将为大多数微阵列社区提供一个标准框架,以比较和改进与微阵列数据分析相关的许多分析和统计方法,包括图像处理,归一化,错误建模,多个报告者的组合每个基因,重复实验的使用以及基于表达变化的测量中的样品参照方案。可用性/补充信息:表达数据和补充信息可在http://www.rii.com/publications/2003/HE_SDS.htm上获得。联系人:yudong_he@merck.com

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