标题： MOST：检测癌症差异基因表达 显示英文标题

标题： MOST: detecting cancer differential gene expression

摘要： 我们提出了一种新的统计方法用于检测当基因仅在样本子集中被激活时的差异表达基因。针对这种非传统情况设计的统计方法已被证明对大多数癌症研究非常有价值，在这些研究中，致癌基因仅在少数疾病样本中被激活。之前在这方面所做的努力包括COPA、OS和ORT。我们提出了一种新的统计方法称为最大有序子集t统计量（MOST），当激活样本的数量未知时，这种方法似乎很自然。我们将MOST与其他统计方法进行了比较，发现所提出的方法通常比其竞争对手具有更高的功效。 显示英文摘要

摘要： We propose a new statistics for the detection of differentially expressed genes, when the genes are activated only in a subset of the samples. Statistics designed for this unconventional circumstance has proved to be valuable for most cancer studies, where oncogenes are activated for a small number of disease samples. Previous efforts made in this direction include COPA, OS and ORT. We propose a new statistics called maximum ordered subset t-statistics (MOST) which seems to be natural when the number of activated samples is unknown. We compare MOST to other statistics and find the proposed method often has more power then its competitors.