Toward a gold standard for promoter prediction evaluation.
Toward a gold standard for promoter prediction evaluation.
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DOI：
10.1093/bioinformatics/btp191
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发表时间：
2009-06-15
期刊：
影响因子：
--
通讯作者：
Saeys Y
中科院分区：
文献类型：
--
作者：
Abeel T;Van de Peer Y;Saeys Y
动机：启动子预测是基因组注释计划中的一项重要任务，近年来出现了许多新的启动子预测程序。然而，这些程序中的许多程序与其他程序相比并不充分。在大多数情况下，只有一小部分基因组被用于评估程序，这对于全基因组注释项目来说是不现实的。此外，仍然缺乏适当比较购买力平价的共同评价设计。结果：我们提出了一个大规模的基准研究的17个国家的最先进的购买力平价。提出了一种多方面的评估策略，可以作为启动子预测评估的金标准，使启动子预测软件的作者能够以适当的方式将他们的方法与现有方法进行比较。随后使用这种评估策略来比较所选择的启动子预测因子，并对预测性能、启动子类别特异性、预测因子之间的重叠和预测的位置偏差进行深入分析。可用性：我们提供四个协议的实现，以及执行基准所需的数据集，以学术界免费的要求。联系方式：yves. psb.ugent.be补充信息：补充数据可在生物信息学在线获得。
Motivation: Promoter prediction is an important task in genome annotation projects, and during the past years many new promoter prediction programs (PPPs) have emerged. However, many of these programs are compared inadequately to other programs. In most cases, only a small portion of the genome is used to evaluate the program, which is not a realistic setting for whole genome annotation projects. In addition, a common evaluation design to properly compare PPPs is still lacking. Results: We present a large-scale benchmarking study of 17 state-of-the-art PPPs. A multi-faceted evaluation strategy is proposed that can be used as a gold standard for promoter prediction evaluation, allowing authors of promoter prediction software to compare their method to existing methods in a proper way. This evaluation strategy is subsequently used to compare the chosen promoter predictors, and an in-depth analysis on predictive performance, promoter class specificity, overlap between predictors and positional bias of the predictions is conducted. Availability: We provide the implementations of the four protocols, as well as the datasets required to perform the benchmarks to the academic community free of charge on request. Contact: yves.vandepeer@psb.ugent.be Supplementary information: Supplementary data are available at Bioinformatics online.
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