Background and Objective: The massive parallel sequencing technology facilitates new discoveries in terms of transcript differential analysis; however, all the new findings must be validated, since the diversity of transcript expression may impair the identification of the most relevant ones. Methods: The proposed RLeave algorithm (implemented in the R environment) utilizes a combination of conventional analysis (classic edgeR) together with other mathematical methods (Leave-one-out sample technique and Decision Trees validation) to identify more relevant candidates to be in vitro or in silico validated. Results: The RLeave protocol was tested using miRNome expression analysis of two sample groups (diabetes mellitus and acute lymphoblastic leukemia), and both had their most important differentially expressed miRNA confirmed by RT-qPCR. Conclusion: This protocol is applicable in RNA-SEQ research, highlighting the most relevant transcripts for in silico and/or in vitro validation.

中文翻译：

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RLeave：用于转录差异表达分析的计算机交叉验证协议

背景与目的：大规模并行测序技术促进了转录差异分析方面的新发现。但是，所有新发现都必须经过验证，因为转录表达的多样性可能会损害最相关的表达。方法：提出的RLeave算法（在R环境中实现）结合了常规分析（经典edgeR）和其他数学方法（留一法样本技术和决策树验证）的组合，以识别更多相关的体外候选者或经过计算机验证。结果：使用两个样品组（糖尿病和急性淋巴细胞白血病）的miRNome表达分析对RLeave方案进行了测试，并且RT-qPCR证实了这两个样品中最重要的差异表达miRNA。结论：