As the amount of sequencing efforts and genomic data volume continue to increase at an accelerated rate, phylogenetic analysis provides an evolutionary context for understanding and interpreting this growing set of complex data. We introduce a novel quartet based method for inferring molecular based phylogeny called hypercleaning{sup}* (HC{sup}*). The HC{sup}* method is based on the hypercleaning (HC) technique, which possesses an interesting property of recovering edges (of a phylogenetic tree) that are best supported by the witness quartet set. HC{sup}* extends HC in two regards: (i) whereas HC constrains the input quartet set to be unweighted (binary valued), HC{sup}* allows any positive valued quartet scores, enabling more informative quartets to be defined, (ii) HC{sup}* employs a novel collapsing technique which significantly speeds up the inference stage, making it empirically on par with quartet puzzling in terms of speed, while still guaranteeing optimal edge recovery as in HC. This paper is primarily aimed at presenting the algorithmic construction of HC{sup}*. We also report some preliminary studies on an implementation of HC{sup}* as a potentially powerful approximation scheme for maximum likelihood based inference. Details of proofs can be found in report at: (www.michaelhu.com/reports/mmath_thesis.pdf).
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机译：随着测序工作量和基因组数据量的不断增加，系统发育分析为理解和解释这种不断增长的复杂数据集提供了进化背景。我们介绍了一种基于四重态的新方法来推断基于分子的系统发育，称为超净{sup} *（HC {sup} *）。 HC {sup} *方法基于超清洁（HC）技术，该技术具有恢复（系统树的）边缘的有趣属性，该边缘最好得到证人四重奏组的支持。 HC {sup} *在两个方面扩展了HC：（i）HC约束输入四重奏组未加权（二值），HC {sup} *允许任何正值四重奏得分，从而可以定义更多信息四重奏; ii）HC {sup} *采用了一种新颖的折叠技术，该技术可以显着加快推理阶段，从经验上讲，它与四重奏令人费解，在速度上仍可保持一致，同时仍能像HC一样保证最佳的边缘恢复。本文的主要目的是介绍HC {sup} *的算法构造。我们还报告了一些关于HC {sup} *的实现的初步研究，这些实现可能是基于最大似然性的潜在强大的近似方案。有关证明的详细信息，请参见以下报告：（www.michaelhu.com/reports/mmath_thesis.pdf）。
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