Estimating the statistical significance of gene expression changes observed with oligonucleotide arrays.
Estimating the statistical significance of gene expression changes observed with oligonucleotide arrays.
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DOI：
10.1093/hmg/11.19.2207
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发表时间：
2002-09
影响因子：
3.5
通讯作者：
A. Strand;J. Olson;C. Kooperberg
中科院分区：
文献类型：
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作者：
A. Strand;J. Olson;C. Kooperberg
我们提出了一种简单的方法，为使用 Affymetrix 寡核苷酸阵列和软件检测到的基因表达变化分配近似 P 值。该方法汇集了基因组的数据和少量的相似比较，以便估计在实验感兴趣的比较中观察到的单个基因变化的显着性。统计显着性水平基于观察到的大多数探针对的变异性，这些变异性表明技术重复比较中差异表达的增加或减少。根据此参考分布或误差模型，我们计算 N > 或 = 2 的比较中分数多数的预期频率。这些计算出的分布是实验比较中所见变化的 P 值估计的来源。该方法旨在补充 Affymetrix 软件，并使涉及有限复制的实验设计的基因选择合理化。
We present a simple method to assign approximate P-values to gene expression changes detected with Affymetrix oligonucleotide arrays and software. The method pools data for groups of genes and a small number of like-to-like comparisons in order to estimate the significance of changes observed for single genes in comparisons of experimental interest. Statistical significance levels are based on the observed variability in the fractional majority of probe pairs that indicate increasing or decreasing differential expression in comparisons of technical replicates. From this reference distribution or error model, we compute the expected frequency for fractional majorities in comparisons for N > or = 2. These computed distributions are the source of P-value estimates for changes seen in the experimental comparisons. The method is intended to complement the Affymetrix software and to rationalize gene selection for experimental designs involving limited replication.