Mapping gene expression quantitative trait loci by singular value decomposition and independent component analysis.
Mapping gene expression quantitative trait loci by singular value decomposition and independent component analysis.
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通过单数值分解和独立的成分分析来映射基因表达定量特质基因座。
DOI：
10.1186/1471-2105-9-244
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发表时间：
2008-05-20
影响因子：
3
通讯作者：
Akey, Joshua M.
中科院分区：
文献类型：
--
作者：
Biswas, Shameek;Storey, John D.;Akey, Joshua M.
基因表达谱与连锁分析的结合已成为基因表达数量性状位点（eQTL）定位的有力范例。迄今为止，大多数研究都是通过逐个分析基因表达特征来寻找eQTL。由于通常要分析数千种表达特征，这可以减少功率，因为需要纠正所执行的假设检验的数量。此外，基因表达性状表现出复杂的相关结构，这在单独分析性状时被忽略了。为了解决这些问题，我们应用了两种不同的多元降维技术，奇异值分解（SVD）和独立成分分析（ICA）对两株酿酒酵母杂交的基因表达特征进行了分析。这两种方法都将数据分解为一组元特征，这些元特征是所有表达特征的线性组合。基因本体的元性状包括代谢途径、应激反应、RNA加工、离子转运、逆转录转位和端粒维持等。对两种技术的前20个元性状进行全基因组连锁分析。共发现21个eQTL，其中11个为新发现。有趣的是，观察到与元特征的顺式和反式联系。这些结果表明，降维方法是探索基因表达变异遗传结构的一种有用和互补的方法。
The combination of gene expression profiling with linkage analysis has become a powerful paradigm for mapping gene expression quantitative trait loci (eQTL). To date, most studies have searched for eQTL by analyzing gene expression traits one at a time. As thousands of expression traits are typically analyzed, this can reduce power because of the need to correct for the number of hypothesis tests performed. In addition, gene expression traits exhibit a complex correlation structure, which is ignored when analyzing traits individually. To address these issues, we applied two different multivariate dimension reduction techniques, the Singular Value Decomposition (SVD) and Independent Component Analysis (ICA) to gene expression traits derived from a cross between two strains of Saccharomyces cerevisiae. Both methods decompose the data into a set of meta-traits, which are linear combinations of all the expression traits. The meta-traits were enriched for several Gene Ontology categories including metabolic pathways, stress response, RNA processing, ion transport, retro-transposition and telomeric maintenance. Genome-wide linkage analysis was performed on the top 20 meta-traits from both techniques. In total, 21 eQTL were found, of which 11 are novel. Interestingly, both cis and trans-linkages to the meta-traits were observed. These results demonstrate that dimension reduction methods are a useful and complementary approach for probing the genetic architecture of gene expression variation.
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影响因子：
12.3
作者：
Lee SI;Batzoglou S
通讯作者：
Batzoglou S
使用主要成分探索多效性。
影响因子：
2.9
作者：
Bensen, JT;Lange, LA;Langefeld, CD;Chang, BL;Bleecker, ER;Meyers, DA;Xu, JF
通讯作者：
Xu, JF
影响因子：
3
作者：
Frigyesi A;Veerla S;Lindgren D;Höglund M
通讯作者：
Höglund M
影响因子：
7.8
作者：
Hyvärinen, A;Oja, E
通讯作者：
Oja, E
影响因子：
3.3
作者：
Bing, N;Hoeschele, I
通讯作者：
Hoeschele, I