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一种新颖的动态冲击分析(DIA)方法,用于时间序列组学研究的功能分析:使用牛乳腺转录组进行验证。

A novel dynamic impact approach (DIA) for functional analysis of time-course omics studies: validation using the bovine mammary transcriptome.

机构信息

Department of Animal Sciences, University of Illinois, Urbana, Illinois, United States of America.

出版信息

PLoS One. 2012;7(3):e32455. doi: 10.1371/journal.pone.0032455. Epub 2012 Mar 16.

Abstract

The overrepresented approach (ORA) is the most widely-accepted method for functional analysis of microarray datasets. The ORA is computationally-efficient and robust; however, it suffers from the inability of comparing results from multiple gene lists particularly with time-course experiments or those involving multiple treatments. To overcome such limitation a novel method termed Dynamic Impact Approach (DIA) is proposed. The DIA provides an estimate of the biological impact of the experimental conditions and the direction of the impact. The impact is obtained by combining the proportion of differentially expressed genes (DEG) with the log2 mean fold change and mean -log P-value of genes associated with the biological term. The direction of the impact is calculated as the difference of the impact of up-regulated DEG and down-regulated DEG associated with the biological term. The DIA was validated using microarray data from a time-course experiment of bovine mammary gland across the lactation cycle. Several annotation databases were analyzed with DIA and compared to the same analysis performed by the ORA. The DIA highlighted that during lactation both BTA6 and BTA14 were the most impacted chromosomes; among Uniprot tissues those related with lactating mammary gland were the most positively-impacted; within KEGG pathways 'Galactose metabolism' and several metabolism categories related to lipid synthesis were among the most impacted and induced; within Gene Ontology "lactose biosynthesis" among Biological processes and "Lactose synthase activity" and "Stearoyl-CoA 9-desaturase activity" among Molecular processes were the most impacted and induced. With the exception of the terms 'Milk', 'Milk protein' and 'Mammary gland' among Uniprot tissues and SP_PIR_Keyword, the use of ORA failed to capture as significantly-enriched (i.e., biologically relevant) any term known to be associated with lactating mammary gland. Results indicate the DIA is a biologically-sound approach for analysis of time-course experiments. This tool represents an alternative to ORA for functional analysis.

摘要

过代表方法(ORA)是最广泛接受的微阵列数据集功能分析方法。ORA 计算效率高且稳健;然而,它无法比较来自多个基因列表的结果,特别是在涉及时间过程或多个处理的情况下。为了克服这种局限性,提出了一种新的方法,称为动态影响方法(DIA)。DIA 提供了对实验条件的生物学影响和影响方向的估计。影响是通过将差异表达基因(DEG)的比例与与生物学术语相关的基因的 log2 平均倍数变化和平均-logP 值相结合来获得的。影响的方向是通过计算与生物学术语相关的上调 DEG 和下调 DEG 的影响之差来计算的。使用牛乳腺在泌乳周期内的时间过程实验的微阵列数据验证了 DIA。使用 DIA 分析了几个注释数据库,并将其与 ORA 执行的相同分析进行了比较。DIA 强调,在泌乳期间,BTA6 和 BTA14 是受影响最大的染色体;在 Uniprot 组织中,与泌乳乳腺相关的组织受影响最大;在 KEGG 途径中,“半乳糖代谢”和与脂质合成相关的几个代谢类别是受影响最大和诱导的途径之一;在基因本体论中,“乳糖生物合成”是生物过程中最受影响和诱导的,“乳糖合酶活性”和“硬脂酰辅酶 A9-去饱和酶活性”是分子过程中最受影响和诱导的。除了 Uniprot 组织中的“牛奶”、“牛奶蛋白”和“乳腺”术语以及 SP_PIR_Keyword 外,ORA 的使用未能捕获任何已知与泌乳乳腺相关的术语,这些术语的富集程度不高(即生物学上相关)。结果表明,DIA 是分析时间过程实验的一种生物学上合理的方法。该工具是 ORA 进行功能分析的替代方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/34a1/3306320/36302c067745/pone.0032455.g001.jpg

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