Microarray experimental design: power and sample size considerations
1 Department of Statistics, University of Florida, Gainesville, Florida 32611 2 Center for Biotechnology and Genomic Medicine, Medical College of Georgia, Augusta, Georgia 30912 Gene expression analysis using high-throughput microarray technology has become a powerful approach to study systems biolo...
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| Veröffentlicht in: | Physiological genomics 2003-12, Vol.16 (1), p.24-28 |
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| creator | Yang, M. C. K Yang, J. J McIndoe, R. A She, J. X |
| description | 1 Department of Statistics, University of Florida, Gainesville, Florida 32611
2 Center for Biotechnology and Genomic Medicine, Medical College of Georgia, Augusta, Georgia 30912
Gene expression analysis using high-throughput microarray technology has become a powerful approach to study systems biology. The exponential growth in microarray experiments has spawned a number of investigations into the reliability and reproducibility of this type of data. However, the sample size requirements necessary to obtain statistically significant results has not had as much attention. We report here statistical methods for the determination of the sufficient number of subjects necessary to minimize the false discovery rate while maintaining high power to detect differentially expressed genes. Two experimental designs were considered: 1 ) a comparison between two groups at a single time point, and 2 ) a comparison of two experimental groups with sequential time points. Computer programs are available for the methods discussed in this paper and are adaptable to more complicated situations.
gene expression; statistical analysis; functional genomics |
| doi_str_mv | 10.1152/physiolgenomics.00037.2003 |
| format | Article |
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2 Center for Biotechnology and Genomic Medicine, Medical College of Georgia, Augusta, Georgia 30912
Gene expression analysis using high-throughput microarray technology has become a powerful approach to study systems biology. The exponential growth in microarray experiments has spawned a number of investigations into the reliability and reproducibility of this type of data. However, the sample size requirements necessary to obtain statistically significant results has not had as much attention. We report here statistical methods for the determination of the sufficient number of subjects necessary to minimize the false discovery rate while maintaining high power to detect differentially expressed genes. Two experimental designs were considered: 1 ) a comparison between two groups at a single time point, and 2 ) a comparison of two experimental groups with sequential time points. Computer programs are available for the methods discussed in this paper and are adaptable to more complicated situations.
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2 Center for Biotechnology and Genomic Medicine, Medical College of Georgia, Augusta, Georgia 30912
Gene expression analysis using high-throughput microarray technology has become a powerful approach to study systems biology. The exponential growth in microarray experiments has spawned a number of investigations into the reliability and reproducibility of this type of data. However, the sample size requirements necessary to obtain statistically significant results has not had as much attention. We report here statistical methods for the determination of the sufficient number of subjects necessary to minimize the false discovery rate while maintaining high power to detect differentially expressed genes. Two experimental designs were considered: 1 ) a comparison between two groups at a single time point, and 2 ) a comparison of two experimental groups with sequential time points. Computer programs are available for the methods discussed in this paper and are adaptable to more complicated situations.
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2 Center for Biotechnology and Genomic Medicine, Medical College of Georgia, Augusta, Georgia 30912
Gene expression analysis using high-throughput microarray technology has become a powerful approach to study systems biology. The exponential growth in microarray experiments has spawned a number of investigations into the reliability and reproducibility of this type of data. However, the sample size requirements necessary to obtain statistically significant results has not had as much attention. We report here statistical methods for the determination of the sufficient number of subjects necessary to minimize the false discovery rate while maintaining high power to detect differentially expressed genes. Two experimental designs were considered: 1 ) a comparison between two groups at a single time point, and 2 ) a comparison of two experimental groups with sequential time points. Computer programs are available for the methods discussed in this paper and are adaptable to more complicated situations.
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| source | MEDLINE; American Physiological Society; EZB-FREE-00999 freely available EZB journals |
| subjects | Oligonucleotide Array Sequence Analysis - methods Reproducibility of Results Research Design Sample Size Statistics as Topic Time Factors |
| title | Microarray experimental design: power and sample size considerations |
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