Multilevel omic data integration in cancer cell lines: advanced annotation and emergent properties.
Multilevel omic data integration in cancer cell lines: advanced annotation and emergent properties.
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癌细胞系中的多级组学数据整合：高级注释和新兴特性
DOI：
10.1186/1752-0509-7-14
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发表时间：
2013-02-19
影响因子：
--
通讯作者：
Nardini C
中科院分区：
文献类型：
--
作者：
Liu Y;Devescovi V;Chen S;Nardini C
由于技术进步、成本降低和精度提高，高通量数据在数量和使用频率上都变得更加普遍。因此，计算科学家面临着两个并行的挑战：一方面，设计有效的方法来解释这些数据中的每一个（基因表达特征，蛋白质标记等）。另一方面，实现了生物学领域的一个新的、紧迫的要求，即设计允许将这些数据作为一个整体进行解释的方法，即不仅作为这些层中每个层中相关分子的联合，而且作为一个复杂的分子包含蛋白质、mRNA和miRNA的分子特征，所有这些都必须直接与能够捕捉层间联系和复杂性的分析结果相关联。我们通过在一个已知的癌症基准上测试一种综合方法来解决这两个挑战中的后一个：NCI-60细胞组。在这里，mRNA，miRNA和蛋白质的高通量筛选使用因子分析结合线性判别分析进行联合分析，以确定癌症的分子特征。与单独（非联合）分析的比较表明，所提出的综合方法可以揭示更深层次和更精确的生物信息。特别是，整合的方法提供了一个更完整的图片的一组miRNAs的鉴定和Wnt途径，这代表了一个重要的替代标志物的黑色素瘤进展。我们进一步在更具挑战性的患者数据集上测试该方法，我们能够识别临床相关的标志物。组学的多个层次的整合可以带来更多的信息，而不是单独的单一层次的分析。使用和扩展所提出的整合框架来整合来自其他分子水平的组学数据，将使研究人员能够发现更多的系统信息。这种方法在临床上具有挑战性的数据集的应用显示出其有前途的潜力。
High-throughput (omic) data have become more widespread in both quantity and frequency of use, thanks to technological advances, lower costs and higher precision. Consequently, computational scientists are confronted by two parallel challenges: on one side, the design of efficient methods to interpret each of these data in their own right (gene expression signatures, protein markers, etc.) and, on the other side, realization of a novel, pressing request from the biological field to design methodologies that allow for these data to be interpreted as a whole, i.e. not only as the union of relevant molecules in each of these layers, but as a complex molecular signature containing proteins, mRNAs and miRNAs, all of which must be directly associated in the results of analyses that are able to capture inter-layers connections and complexity. We address the latter of these two challenges by testing an integrated approach on a known cancer benchmark: the NCI-60 cell panel. Here, high-throughput screens for mRNA, miRNA and proteins are jointly analyzed using factor analysis, combined with linear discriminant analysis, to identify the molecular characteristics of cancer. Comparisons with separate (non-joint) analyses show that the proposed integrated approach can uncover deeper and more precise biological information. In particular, the integrated approach gives a more complete picture of the set of miRNAs identified and the Wnt pathway, which represents an important surrogate marker of melanoma progression. We further test the approach on a more challenging patient-dataset, for which we are able to identify clinically relevant markers. The integration of multiple layers of omics can bring more information than analysis of single layers alone. Using and expanding the proposed integrated framework to integrate omic data from other molecular levels will allow researchers to uncover further systemic information. The application of this approach to a clinically challenging dataset shows its promising potential.
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DOI：
10.1038/jid.2008.445
发表时间：
2009-07
期刊：
The Journal of investigative dermatology
影响因子：
--
作者：
Chien AJ;Conrad WH;Moon RT
通讯作者：
Moon RT
影响因子：
15.8
作者：
Ahn AC;Tewari M;Poon CS;Phillips RS
通讯作者：
Phillips RS
影响因子：
3.6
作者：
Fernandez, Lara P.;Milne, Roger L.;Ribas, Gloria
通讯作者：
Ribas, Gloria
影响因子：
5.7
作者：
Blower, Paul E.;Verducci, Joseph S.;Sadee, Wolfgang
通讯作者：
Sadee, Wolfgang
影响因子：
4
作者：
Kelly ZL;Michael A;Butler-Manuel S;Pandha HS;Morgan RG
通讯作者：
Morgan RG