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AffyMiner：挖掘基因芯片微阵列数据中的差异表达基因和生物学知识。

AffyMiner: mining differentially expressed genes and biological knowledge in GeneChip microarray data.

作者信息

Lu Guoqing, Nguyen The V, Xia Yuannan, Fromm Michael

机构信息

Department of Biology, University of Nebraska, Omaha, NE 68182, USA.

出版信息

BMC Bioinformatics. 2006 Dec 12;7 Suppl 4(Suppl 4):S26. doi: 10.1186/1471-2105-7-S4-S26.

DOI:10.1186/1471-2105-7-S4-S26
PMID:17217519
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC1780108/
Abstract

BACKGROUND

DNA microarrays are a powerful tool for monitoring the expression of tens of thousands of genes simultaneously. With the advance of microarray technology, the challenge issue becomes how to analyze a large amount of microarray data and make biological sense of them. Affymetrix GeneChips are widely used microarrays, where a variety of statistical algorithms have been explored and used for detecting significant genes in the experiment. These methods rely solely on the quantitative data, i.e., signal intensity; however, qualitative data are also important parameters in detecting differentially expressed genes.

RESULTS

AffyMiner is a tool developed for detecting differentially expressed genes in Affymetrix GeneChip microarray data and for associating gene annotation and gene ontology information with the genes detected. AffyMiner consists of the functional modules, GeneFinder for detecting significant genes in a treatment versus control experiment and GOTree for mapping genes of interest onto the Gene Ontology (GO) space; and interfaces to run Cluster, a program for clustering analysis, and GenMAPP, a program for pathway analysis. AffyMiner has been used for analyzing the GeneChip data and the results were presented in several publications.

CONCLUSION

AffyMiner fills an important gap in finding differentially expressed genes in Affymetrix GeneChip microarray data. AffyMiner effectively deals with multiple replicates in the experiment and takes into account both quantitative and qualitative data in identifying significant genes. AffyMiner reduces the time and effort needed to compare data from multiple arrays and to interpret the possible biological implications associated with significant changes in a gene's expression.

摘要

背景

DNA微阵列是一种能够同时监测数万个基因表达的强大工具。随着微阵列技术的发展，面临的挑战问题变成了如何分析大量的微阵列数据并从中获得生物学意义。Affymetrix基因芯片是广泛使用的微阵列，已经探索了多种统计算法并用于检测实验中的显著基因。这些方法仅依赖于定量数据，即信号强度；然而，定性数据在检测差异表达基因时也是重要的参数。

结果

AffyMiner是一种用于检测Affymetrix基因芯片微阵列数据中差异表达基因，并将基因注释和基因本体信息与检测到的基因相关联的工具。AffyMiner由功能模块组成，包括在处理组与对照组实验中检测显著基因的GeneFinder，以及将感兴趣的基因映射到基因本体（GO）空间的GOTree；还有运行用于聚类分析的程序Cluster和用于通路分析的程序GenMAPP的接口。AffyMiner已用于分析基因芯片数据，其结果在多篇出版物中呈现。

结论

AffyMiner填补了在Affymetrix基因芯片微阵列数据中寻找差异表达基因方面的一个重要空白。AffyMiner有效地处理实验中的多个重复样本，并在识别显著基因时兼顾了定量和定性数据。AffyMiner减少了比较多个阵列数据以及解释与基因表达显著变化相关的可能生物学意义所需的时间和精力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c115/1780108/f4feb6365ae4/1471-2105-7-S4-S26-8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c115/1780108/1b37385b1dc1/1471-2105-7-S4-S26-1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c115/1780108/6b3eb4e8836a/1471-2105-7-S4-S26-2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c115/1780108/8435ee721af2/1471-2105-7-S4-S26-3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c115/1780108/52b8b1fec459/1471-2105-7-S4-S26-4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c115/1780108/4ad3ac9583ec/1471-2105-7-S4-S26-5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c115/1780108/ec86f60c3142/1471-2105-7-S4-S26-6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c115/1780108/c0f51765ee6b/1471-2105-7-S4-S26-7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c115/1780108/f4feb6365ae4/1471-2105-7-S4-S26-8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c115/1780108/1b37385b1dc1/1471-2105-7-S4-S26-1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c115/1780108/6b3eb4e8836a/1471-2105-7-S4-S26-2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c115/1780108/8435ee721af2/1471-2105-7-S4-S26-3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c115/1780108/52b8b1fec459/1471-2105-7-S4-S26-4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c115/1780108/4ad3ac9583ec/1471-2105-7-S4-S26-5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c115/1780108/ec86f60c3142/1471-2105-7-S4-S26-6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c115/1780108/c0f51765ee6b/1471-2105-7-S4-S26-7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c115/1780108/f4feb6365ae4/1471-2105-7-S4-S26-8.jpg

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2
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3
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4
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Proc Natl Acad Sci U S A. 2006 Apr 11;103(15):6049-54. doi: 10.1073/pnas.0600944103. Epub 2006 Apr 3.
5
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