GATHER: a systems approach to interpreting genomic signatures
GATHER: a systems approach to interpreting genomic signatures
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DOI：
10.1093/bioinformatics/btl483
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发表时间：
2006-12-01
期刊：
影响因子：
5.8
通讯作者：
Nevins, Joseph R.
中科院分区：
文献类型：
--
作者：
Chang, Jeffrey T.;Nevins, Joseph R.
动机：在整个生物系统的背景下，理解分子图谱中捕捉到的生物学的全部含义，不是简单地检查签名中的单个基因就能实现的。为了促进这一理解，我们开发了GATHER，这是一个集成了各种形式的可用数据来阐明高通量后基因组分析产生的分子签名中的生物学背景的工具。结果：分析RB/E2F肿瘤抑制因子途径，我们发现GATE识别该途径的关键特征。我们进一步表明，GATE在一系列原本无关的基因表达特征中识别出共同的生物学，每个基因表达特征都预测乳腺癌的结果。我们量化了GATHER的性能，发现它成功地预测了广泛基因组上90%的功能。我们认为，GATHER为从基因组规模分析产生的分子签名中提取全部价值提供了一个必要的工具。
Motivation: Understanding the full meaning of the biology captured in molecular profiles, within the context of the entire biological system, cannot be achieved with a simple examination of the individual genes in the signature. To facilitate such an understanding, we have developed GATHER, a tool that integrates various forms of available data to elucidate biological context within molecular signatures produced from high-throughput post-genomic assays.Results: Analyzing the Rb/E2F tumor suppressor pathway, we show that GATHER identifies critical features of the pathway. We further show that GATHER identifies common biology in a series of otherwise unrelated gene expression signatures that each predict breast cancer outcome. We quantify the performance of GATHER and find that it successfully predicts 90% of the functions over a broad range of gene groups. We believe that GATHER provides an essential tool for extracting the full value from molecular signatures generated from genome-scale analyses.