Balancing the robustness and predictive performance of biomarkers.

Balancing the robustness and predictive performance of biomarkers.
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DOI:
10.1089/cmb.2013.0018
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发表时间:
2013-12
期刊:
Journal of computational biology : a journal of computational molecular cell biology
影响因子:
--
通讯作者:
Stumpf MP
Stumpf MP
中科院分区:
其他
文献类型:
--
作者:
Kirk P;Witkover A;Bangham CR;Richardson S;Lewin AM;Stumpf MP

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最近的研究强调了评估从实验数据中确定的假定生物标志物的稳健性的重要性。这就产生了稳定生物标志物的概念,即无论数据的微小扰动如何都能始终识别的生物标志物。由于稳定性本身并不是一个有用的目标,我们提出了一些结合稳定性评估和预测性能的策略,以确定既稳健又诊断有用的生物标志物。此外,通过围绕由弹性网惩罚规范化的逻辑回归分类器包装这些策略,我们能够评估生物标志物之间的相关性对其感知稳定性的影响。我们用一个综合的例子来说明我们提出的策略的性质。在这个例子中,我们发现:(i)稳定性评估可以帮助减少假阳性生物标志物的数量,尽管可能以错过一些真阳性为代价;(ii)将稳定性评估与预测性能评估相结合可以提高真阳性率;(iii)生物标志物之间的相关性可能对其稳定性产生不利影响,因此在进行生物标志物发现时必须仔细考虑。然后,我们将我们的策略应用于蛋白质组学背景,以确定人类疾病htlv1相关脊髓病/热带痉挛性截瘫(HAM/TSP)的一些强大的候选生物标志物。
Recent studies have highlighted the importance of assessing the robustness of putative biomarkers identified from experimental data. This has given rise to the concept of stable biomarkers, which are ones that are consistently identified regardless of small perturbations to the data. Since stability is not by itself a useful objective, we present a number of strategies that combine assessments of stability and predictive performance in order to identify biomarkers that are both robust and diagnostically useful. Moreover, by wrapping these strategies around logistic regression classifiers regularised by the elastic net penalty, we are able to assess the effects of correlations between biomarkers upon their perceived stability. We use a synthetic example to illustrate the properties of our proposed strategies. In this example, we find that: (i) assessments of stability can help to reduce the number of false positive biomarkers, although potentially at the cost of missing some true positives; (ii) combining assessments of stability with assessments of predictive performance can improve the true positive rate; and (iii) correlations between biomarkers can have adverse effects on their stability, and hence must be carefully taken into account when undertaking biomarker discovery. We then apply our strategies in a proteomics context, in order to identify a number of robust candidate biomarkers for the human disease HTLV1-associated myelopathy/tropical spastic paraparesis (HAM/TSP).
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