Boes T, Neuhäuser M
Institut für Medizinische Informatik, Biometrie und Epidemiologie, Universitätsklinikum Essen, Hufelandstr. 55, 45122 Essen, Germany.
Methods Inf Med. 2005;44(3):414-7.
The high density oligonucleotide microarrays from Affymetrix (Affymetrix GeneChips) are very popular in biomedical research. They enable to study the expression of thousands of genes simultaneously. In experiments with multiple arrays, normalization techniques are used to reduce the so-called obscuring variation, i.e. the technical variation that is of non-biological origin. Several different normalization methods have been proposed during the last years.
We review published results about the comparison of normalization methods proposed for Affymetrix GeneChips.
The quantile normalization seems to perform favorably regarding precision (low variance), accuracy (low bias), and practicability (low computing time). However, according to very recent results, this normalization method can have an impact on the biological variability and, therefore, appears to be less than optimal from this point of view.
Although the quantile normalization may be recommendable, more investigations based on more data sets are needed so that the different normalization methods can be evaluated on widely differing data.
Affymetrix公司的高密度寡核苷酸微阵列(Affymetrix基因芯片)在生物医学研究中非常受欢迎。它们能够同时研究数千个基因的表达。在多阵列实验中,使用归一化技术来减少所谓的模糊变异,即非生物来源的技术变异。在过去几年中已经提出了几种不同的归一化方法。
我们回顾了关于Affymetrix基因芯片所提出的归一化方法比较的已发表结果。
分位数归一化在精度(低方差)、准确性(低偏差)和实用性(低计算时间)方面似乎表现良好。然而,根据最近的结果,这种归一化方法可能会对生物变异性产生影响,因此,从这个角度来看似乎并非最优。
虽然分位数归一化可能是值得推荐的,但需要基于更多数据集进行更多研究,以便在广泛不同的数据上评估不同的归一化方法。