Processed Saccharomyces cerevisiae transcriptomics and genomics data for machine learning

<strong>Genomic data including open reading frame (ORF) boundaries of Saccharomyces cerevisiae C288 was obtained from the Saccharomyces Genome Database (https://www.yeastgenome.org/) (Cherry, J. M. et al. Saccharomyces Genome Database: the genomics resource of budding yeast. Nucleic Acids Res. 40, D700–5 (2012)) and published data (Xu, Z. et al. Bidirectional promoters generate pervasive transcription in yeast. Nature 457, 1033–1037 (2009), Nagalakshmi, U. et al. The transcriptional landscape of the yeast genome defined by RNA sequencing. Science 320, 1344–1349 (2008)). </strong><strong>Coding regions were extracted based on ORF boundaries and codon frequencies were normalized to probabilities. Processed raw RNA sequencing Star counts were obtained from the Digital Expression Explorer V2 database (http://dee2.io/index.html) (Ziemann, M., Kaspi, A. &amp; El-Osta, A. Digital expression explorer 2: a repository of uniformly processed RNA sequencing data. GigaScience vol. 8 (2019)) and filtered for experiments that passed quality control. Raw mRNA data were transformed to transcripts per million (TPM) counts and genes with zero mRNA output (TPM &lt; 5) were removed. Prior to modeling, the mRNA counts were Box-Cox transformed.</strong>酿酒酵母（Saccharomyces cerevisiae）C288的基因组数据（包含开放阅读框（open reading frame, ORF）边界信息）获取自酿酒酵母基因组数据库（Saccharomyces Genome Database，https://www.yeastgenome.org/），数据来源包括Cherry JM等人发表的研究《Saccharomyces Genome Database: the genomics resource of budding yeast》（发表于《Nucleic Acids Research》2012年第40卷，D700–D705页），以及两项已发表数据集：Xu Z等人于2009年发表于《Nature》第457卷的《Bidirectional promoters generate pervasive transcription in yeast》（第1033–1037页），与Nagalakshmi U等人于2008年发表于《Science》第320卷的《The transcriptional landscape of the yeast genome defined by RNA sequencing》（第1344–1349页）。 研究人员基于ORF边界提取编码区，并将密码子频率归一化为概率分布。经标准化处理的RNA测序STAR计数数据获取自数字表达探索器V2数据库（Digital Expression Explorer V2，http://dee2.io/index.html），该数据集的相关文献为Ziemann M、Kaspi A与El-Osta A发表于《GigaScience》2019年第8卷的《Digital expression explorer 2: a repository of uniformly processed RNA sequencing data》。本研究对该数据库中通过质量控制的实验数据进行筛选，将原始mRNA数据转换为每百万转录本（transcripts per million, TPM）计数，并移除TPM值小于5、即mRNA表达量为0的基因。在建模前，研究人员对mRNA计数数据进行了Box-Cox变换。