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改变的通路分析器:一种用于识别和优先考虑差异调节和网络重布线通路的基因表达数据集分析工具。

Altered Pathway Analyzer: A gene expression dataset analysis tool for identification and prioritization of differentially regulated and network rewired pathways.

机构信息

Translational Bioinformatics Group, International Centre for Genetic Engineering and Biotechnology, New Delhi 110067, India.

Department of Biochemistry, Jamia Hamdard, Deemed University, New Delhi 110062, India.

出版信息

Sci Rep. 2017 Jan 13;7:40450. doi: 10.1038/srep40450.

Abstract

Gene connection rewiring is an essential feature of gene network dynamics. Apart from its normal functional role, it may also lead to dysregulated functional states by disturbing pathway homeostasis. Very few computational tools measure rewiring within gene co-expression and its corresponding regulatory networks in order to identify and prioritize altered pathways which may or may not be differentially regulated. We have developed Altered Pathway Analyzer (APA), a microarray dataset analysis tool for identification and prioritization of altered pathways, including those which are differentially regulated by TFs, by quantifying rewired sub-network topology. Moreover, APA also helps in re-prioritization of APA shortlisted altered pathways enriched with context-specific genes. We performed APA analysis of simulated datasets and p53 status NCI-60 cell line microarray data to demonstrate potential of APA for identification of several case-specific altered pathways. APA analysis reveals several altered pathways not detected by other tools evaluated by us. APA analysis of unrelated prostate cancer datasets identifies sample-specific as well as conserved altered biological processes, mainly associated with lipid metabolism, cellular differentiation and proliferation. APA is designed as a cross platform tool which may be transparently customized to perform pathway analysis in different gene expression datasets. APA is freely available at http://bioinfo.icgeb.res.in/APA.

摘要

基因连接重排是基因网络动态的一个基本特征。除了其正常的功能作用外,它还可能通过干扰途径的动态平衡而导致功能失调的状态。很少有计算工具可以测量基因共表达及其相应调控网络中的重排,以识别和优先考虑可能或不可能受到差异调节的改变途径。我们开发了改变途径分析器(APA),这是一种微阵列数据集分析工具,用于通过量化重排的子网络拓扑结构来识别和优先考虑改变的途径,包括那些受到 TF 差异调节的途径。此外,APA 还有助于重新优先考虑与上下文特定基因富集的 APA 入围改变途径。我们对模拟数据集和 p53 状态 NCI-60 细胞系微阵列数据进行了 APA 分析,以证明 APA 用于识别几种特定于案例的改变途径的潜力。APA 分析揭示了其他评估工具未检测到的几种改变途径。对不相关的前列腺癌数据集的 APA 分析确定了样本特异性和保守的改变生物学过程,主要与脂质代谢、细胞分化和增殖有关。APA 被设计为一个跨平台工具,可以透明地定制以在不同的基因表达数据集中进行途径分析。APA 可在 http://bioinfo.icgeb.res.in/APA 上免费获得。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/19e5/5233954/b68688b700ee/srep40450-f1.jpg

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