Differential expression analysis for pathways.
Differential expression analysis for pathways.
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DOI：
10.1371/journal.pcbi.1002967
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发表时间：
2013
影响因子：
4.3
通讯作者：
Kolker E
中科院分区：
文献类型：
--
作者：
Haynes WA;Higdon R;Stanberry L;Collins D;Kolker E
生命科学技术产生了大量的数据，这些数据掌握着解开重要生物功能和疾病机制秘密的钥匙。我们提出了DEAP，差异表达分析的途径，它利用有关生物途径的信息，以确定重要的监管模式，从差异表达数据。DEAP通过包括有关通路结构的信息并发现通路的最差异表达部分，对现有方法进行了重大改进。在模拟数据上，DEAP显著优于传统方法：对于高差异表达，DEAP将功率提高了两个数量级;对于非常低的差异表达，DEAP将功率提高了一倍。DEAP性能在两个不同的基因和蛋白质表达研究上进行了说明。DEAP发现了14个与慢性阻塞性肺疾病和干扰素治疗相关的重要途径，这些途径是现有方法所忽略的。在干扰素研究中，DEAP将焦点集中在26蛋白Notch信号通路中的4蛋白通路上。数据洪流对生命科学来说是一个日益严峻的挑战。在这片数据的海洋中，肯定隐藏着许多了解重要生物和医学系统的秘密。为了量化这些数据中的重要模式，我们提出了DEAP（通路的差异表达分析）。DEAP融合了生物学途径结构和差异表达的信息，以确定重要的调控模式。在模拟和生物数据上，我们表明DEAP能够识别关键机制，同时对现有方法进行重大改进。例如，在干扰素研究中，DEAP独特地鉴定了干扰素γ信号通路和JAK STAT信号通路。
Life science technologies generate a deluge of data that hold the keys to unlocking the secrets of important biological functions and disease mechanisms. We present DEAP, Differential Expression Analysis for Pathways, which capitalizes on information about biological pathways to identify important regulatory patterns from differential expression data. DEAP makes significant improvements over existing approaches by including information about pathway structure and discovering the most differentially expressed portion of the pathway. On simulated data, DEAP significantly outperformed traditional methods: with high differential expression, DEAP increased power by two orders of magnitude; with very low differential expression, DEAP doubled the power. DEAP performance was illustrated on two different gene and protein expression studies. DEAP discovered fourteen important pathways related to chronic obstructive pulmonary disease and interferon treatment that existing approaches omitted. On the interferon study, DEAP guided focus towards a four protein path within the 26 protein Notch signalling pathway. The data deluge represents a growing challenge for life sciences. Within this sea of data surely lie many secrets to understanding important biological and medical systems. To quantify important patterns in this data, we present DEAP (Differential Expression Analysis for Pathways). DEAP amalgamates information about biological pathway structure and differential expression to identify important patterns of regulation. On both simulated and biological data, we show that DEAP is able to identify key mechanisms while making significant improvements over existing methodologies. For example, on the interferon study, DEAP uniquely identified both the interferon gamma signalling pathway and the JAK STAT signalling pathway.
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影响因子：
12.3
作者：
Hung JH;Whitfield TW;Yang TH;Hu Z;Weng Z;DeLisi C
通讯作者：
DeLisi C
DOI：
10.2202/1544-6115.1418
发表时间：
2009-01-01
影响因子：
0.9
作者：
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通讯作者：
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影响因子：
7
作者：
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通讯作者：
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影响因子：
9.6
作者：
Esther, Charles R., Jr.;Lazaar, Aili L.;Boucher, Richard C.
通讯作者：
Boucher, Richard C.
影响因子：
7.3
作者：
Gough, Nancy R;Yaffe, Michael B
通讯作者：
Yaffe, Michael B