Fast network component analysis (FastNCA) for gene regulatory network reconstruction from microarray data
Fast network component analysis (FastNCA) for gene regulatory network reconstruction from microarray data
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DOI：
10.1093/bioinformatics/btn131
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发表时间：
2008-06-01
期刊：
影响因子：
5.8
通讯作者：
Fung, Peter Chin Wan
中科院分区：
文献类型：
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作者：
Chang, Chunqi;Ding, Zhi;Fung, Peter Chin Wan
动机：最近发展起来的网络成分分析(NCA)方法有望从微阵列数据中重建基因调控网络。现有的NCA算法是一种迭代方法，存在两个潜在的局限性：计算不稳定性和多个局部解。随后发展的Tikhonov正则化NCA-r算法可以帮助解决第一个问题，但不能完全处理第二个问题。本文提出了一种新的快速网络分量分析(FastNCA)算法，该算法的解析解要快得多，且不受上述限制。结果：首先，使用合成数据将FastNCA与NCA和NCA-r进行了比较。FastNCA重建比NCA-r重建更准确，与适当收敛的NCA重建结果相当。FastNCA对输入信号之间的相关性不敏感，但其性能略有下降，但不像NCA那样显著。与NCA一样，FastNCA对网络拓扑中先验信息中的微小不准确并不十分敏感。FastNCA大约比NCA快几十倍，比NCA-r快几百倍。然后，将该方法应用于实际酵母细胞周期芯片数据。FastNCA和NCA-r估计的细胞周期调控因子的活性与Lee等人独立获得的半定量结果进行了比较。(2002)。结果表明，FastNCA和LEES的结果比NCA-r和LEES的结果有更大的一致性，前者以2333表示，后者为1433。
Motivation: Recently developed network component analysis (NCA) approach is promising for gene regulatory network reconstruction from microarray data. The existing NCA algorithm is an iterative method which has two potential limitations: computational instability and multiple local solutions. The subsequently developed NCA-r algorithm with Tikhonov regularization can help solve the first issue but cannot completely handle the second one. Here we develop a novel Fast Network Component Analysis (FastNCA) algorithm which has an analytical solution that is much faster and does not have the above limitations.Results: Firstly FastNCA is compared to NCA and NCA-r using synthetic data. The reconstruction of FastNCA is more accurate than that of NCA-r and comparable to that of properly converged NCA. FastNCA is not sensitive to the correlation among the input signals, while its performance does degrade a little but not as dramatically as that of NCA. Like NCA, FastNCA is not very sensitive to small inaccuracies in a priori information on the network topology. FastNCA is about several tens times faster than NCA and several hundreds times faster than NCA-r. Then, the method is applied to real yeast cell-cycle microarray data. The activities of the estimated cell-cycle regulators by FastNCA and NCA-r are compared to the semi-quantitative results obtained independently by Lee et al. (2002). It is shown here that there is a greater agreement between the results of FastNCA and Lees, which is represented by the ratio 2333, than that between the results of NCA-r and Lees, which is 1433.