TROM: A Testing-Based Method for Finding Transcriptomic Similarity of Biological Samples.
TROM: A Testing-Based Method for Finding Transcriptomic Similarity of Biological Samples.
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DOI：
10.1007/s12561-016-9163-y
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发表时间：
2017-06
影响因子：
1
通讯作者：
Li JJ
中科院分区：
文献类型：
--
作者：
Li WV;Chen Y;Li JJ
由于高通量技术的发展，包括微阵列和下一代RNA测序，产生了大量的转录组数据，比较转录组学在基因组研究中越来越受欢迎。一个重要的问题是了解不同物种生物过程的保守性和差异性。我们提出了一种基于测试的方法TROM（转录组重叠测量）比较转录组内或不同物种之间，并提供了一个不同的角度来看，在传统的相关性分析，捕获转录组相似性。具体地，TROM方法集中于识别捕获生物样品的分子特征的相关基因，并且随后通过测试其相关基因的重叠来比较生物样品。我们使用模拟和真实的数据研究表明，TROM是更强大的识别相似的转录组和更强大的随机基因表达噪声比皮尔逊和斯皮尔曼相关性。我们应用TROM比较了六种果蝇的发育阶段，C。elegans，S. purpuratus、红腹拟步行虫D. rerio和小鼠肝脏，并发现有趣的对应模式，这意味着保守的基因表达程序在这些物种的发展。TROM方法可作为CRAN（https：//cran.r-project.org/package=TROM）上的R包获得，手册和源代码可在http://www.stat.ucla.edu/~jingyi.li/software-and-data/trom.html获得。
Comparative transcriptomics has gained increasing popularity in genomic research thanks to the development of high-throughput technologies including microarray and next-generation RNA sequencing that have generated numerous transcriptomic data. An important question is to understand the conservation and divergence of biological processes in different species. We propose a testing-based method TROM (Transcriptome Overlap Measure) for comparing transcriptomes within or between different species, and provide a different perspective, in contrast to traditional correlation analyses, about capturing transcriptomic similarity. Specifically, the TROM method focuses on identifying associated genes that capture molecular characteristics of biological samples, and subsequently comparing the biological samples by testing the overlap of their associated genes. We use simulation and real data studies to demonstrate that TROM is more powerful in identifying similar transcriptomes and more robust to stochastic gene expression noise than Pearson and Spearman correlations. We apply TROM to compare the developmental stages of six Drosophila species, C. elegans, S. purpuratus, D. rerio and mouse liver, and find interesting correspondence patterns that imply conserved gene expression programs in the development of these species. The TROM method is available as an R package on CRAN (https://cran.r-project.org/package=TROM) with manuals and source codes available at http://www.stat.ucla.edu/~jingyi.li/software-and-data/trom.html.