Barker Daniel, Meade Andrew, Pagel Mark
Sir Harold Mitchell Building, School of Biology, University of St Andrews St Andrews, Fife, KY16 9TH, UK.
Bioinformatics. 2007 Jan 1;23(1):14-20. doi: 10.1093/bioinformatics/btl558. Epub 2006 Nov 7.
We compare phylogenetic approaches for inferring functional gene links. The approaches detect independent instances of the correlated gain and loss of pairs of genes from species' genomes. We investigate the effect on results of basing evidence of correlations on two phylogenetic approaches, Dollo parsminony and maximum likelihood (ML). We further examine the effect of constraining the ML model by fixing the rate of gene gain at a low value, rather than estimating it from the data.
We detect correlated evolution among a test set of pairs of yeast (Saccharomyces cerevisiae) genes, with a case study of 21 eukaryotic genomes and test data derived from known yeast protein complexes. If the rate at which genes are gained is constrained to be low, ML achieves by far the best results at detecting known functional links. The model then has fewer parameters but it is more realistic by preventing genes from being gained more than once.
BayesTraits by M. Pagel and A. Meade, and a script to configure and repeatedly launch it by D. Barker and M. Pagel, are available at http://www.evolution.reading.ac.uk
我们比较用于推断功能基因联系的系统发育方法。这些方法从物种基因组中检测基因对的相关获得和丢失的独立实例。我们研究基于两种系统发育方法(多洛简约法和最大似然法(ML))的相关性证据对结果的影响。我们进一步研究通过将基因获得率固定在一个较低值而非从数据中估计它来约束ML模型的效果。
我们在一组酵母(酿酒酵母)基因对的测试集中检测到相关进化,以21个真核生物基因组为案例研究,并使用从已知酵母蛋白质复合物获得的测试数据。如果基因获得率被约束为较低值,ML在检测已知功能联系方面取得了迄今为止最好的结果。该模型的参数较少,但通过防止基因多次获得而更符合实际情况。
M. Pagel和A. Meade开发的BayesTraits以及D. Barker和M. Pagel编写的用于配置和重复启动它的脚本可从http://www.evolution.reading.ac.uk获取