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評估高密度寡核苷酸晶片正規化方法

Evaluation of Normalization Methods for the High Density Oligonucleotide Array

摘要


高密度寡核苷酸晶片(high density oligonucleotide array)因其可同時提供大量基因序列相關資訊,因此已被廣泛運用在生物醫學研究上,可用於篩選及監測基因的表現,並對新藥的研發以及疾病產生機制的探索有所貢獻。但實驗的執行通常會需要準備多個晶片,且取得基因表現量的過程會包含樣本準備、晶片標記處理等及掃描儀等設備的操作,這些均會影響觀測到的基因表現量,而造成有誤差觀察資料。因此在進行分析前,基因表現量的資料需先進行正規化,使得該部分的誤差降至最低,以確保後續分析結果的正確性。關於晶片基因表現量的正規化方法,過去許多文獻有進行討論(如Affymetirx, 2001, Li及Wong, 2001, Bolstad等人,2003),但多數文獻僅用簡單的文字敘述來呈現正規化方法的步驟,本文提供三種已被設定在分析基因表現量的軟體正規化方法,分別為尺度正規化(scaling transformation)、不變集正規化(invariant set transformation)、百分位正規化(quantile normalization)的執行方式及使用操作範例,再利用二個經實驗設計設計取得得高密度寡核苷酸晶片資料來比較三種常用於高密度寡核苷酸晶片正規化方法,並使用六種評估指標來衡量三種正規化方法的表現。

並列摘要


The high density oligonucleotide array from Affymetrix is very popular in biomedical research. Since it can provide thousands of gene expressions simultaneously, it can be used to explore the possible association between diseases and gene mutation. When reporting the gene expression, many processing procedures are required such as labeling, hybridization and scanning. Furthermore, multiple arrays may be often needed in an experiment. These may induce variations when observing the expression level and may have significant effects on data. In turn, normalizations are needed to reduce this kind of variation. This paper reviews three well-known normalization techniques for the Affymetrix array including scaling normalization, an invariant set normalization and the quantile normalization. Two well-designed public Affymetrix data are used to illustrate the normalization procedures and six indices are used to evaluate the performance of these normalization methods.

參考文獻


Affymetrix(2001).Statistical algorithms reference guide.Technical report.(Technical report).,未出版Affymetrix.
Bolstad, B. M.(1998).Low-level analysis of high-density oligonucleotide array data: background, normalization and summarization.University of California, Berkeley.
Bolstad, B. M.,Irizarry, R. A.,Astrand, M.,Speed, T. P.(2003).A comparison of normalization methods for high density oligonucleotide array data based on variance and bias.Bioinformatics.19,185-193.
Cope, L. M.,Irizarry, R. A.,Jaffee, H. A.,Wu, Z.,Speed, T. P.(2004).A benchmark for Affymetrix GeneChip expression measures.Bioinformatics.20,323-331.
Dudoit, S.,Yang, Y. H.,Callow, M. J.,Speed, T. P.(2002).Statistical methods for identifying genes with differential expression in replicated cdna microarray experiments.Statistica Sinica.12,111-139.

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