Interpreting the importance of transcript features in protein abundance prediction models

Supplementary Tables S1-S7.<br>Protein and mRNA levels correlate only moderately across samples. The availability of proteogenomics data sets with protein and transcript measurements from matching samples is providing new opportunities to assess the degree to which protein levels in a system can be predicted from mRNA information. We analyzed large proteogenomics datasets from the Clinical Proteomic Tumor Analysis Consortium (CPTAC) containing 13 637 proteins with matching transcriptome data from up to 958 tumor or normal adjacent tissue samples each, and trained models to predict protein abundance from the transcriptome of a sample using different algorithms and feature sets.<br>

补充表S1至S7。不同样本间的蛋白质与mRNA水平仅呈中等程度相关。从匹配样本中同步获取蛋白质与转录本检测数据的蛋白质基因组学（proteogenomics）数据集，为评估通过mRNA信息预测系统内蛋白质水平的可行程度提供了全新契机。本研究分析了来自临床蛋白质组肿瘤分析联盟（Clinical Proteomic Tumor Analysis Consortium, CPTAC）的大型蛋白质基因组学数据集，该数据集涵盖13637种蛋白质，每种蛋白质均配有至多958份肿瘤或邻近正常组织样本的匹配转录组数据；我们采用不同算法与特征集，基于样本转录组训练模型以预测蛋白质丰度。