Table_1_Biomarker Categorization in Transcriptomic Meta-Analysis by Concordant Patterns With Application to Pan-Cancer Studies.xlsx

With the increasing availability and dropping cost of high-throughput technology in recent years, many-omics datasets have accumulated in the public domain. Combining multiple transcriptomic studies on related hypothesis via meta-analysis can improve statistical power and reproducibility over single studies. For differential expression (DE) analysis, biomarker categorization by DE pattern across studies is a natural but critical task following biomarker detection to help explain between study heterogeneity and classify biomarkers into categories with potentially related functionality. In this paper, we propose a novel meta-analysis method to categorize biomarkers by simultaneously considering the concordant pattern and the biological and statistical significance across studies. Biomarkers with the same DE pattern can be analyzed together in downstream pathway enrichment analysis. In the presence of different types of transcripts (e.g., mRNA, miRNA, and lncRNA, etc.), integrative analysis including miRNA/lncRNA target enrichment analysis and miRNA-mRNA and lncRNA-mRNA causal regulatory network analysis can be conducted jointly on all the transcripts of the same category. We applied our method to two Pan-cancer transcriptomic study examples with single or multiple types of transcripts available. Targeted downstream analysis identified categories of biomarkers with unique functionality and regulatory relationships that motivate new hypothesis in Pan-cancer analysis.

近年来，随着高通量技术（high-throughput technology）的可及性持续提升、成本不断下降，公共领域已积累了海量多组学数据集。通过元分析（meta-analysis）整合针对相关假说的多项转录组学研究，可比单一研究获得更高的统计效力与可重复性。在差异表达分析（differential expression, DE）中，基于跨研究DE模式对生物标志物（biomarker）进行分类，是生物标志物检测后一项自然却关键的任务——该任务可用于阐释研究间异质性，并将生物标志物划分为功能潜在相关的类别。本文提出一种新型元分析方法，可通过同时考量跨研究的一致模式、生物学意义与统计显著性，实现生物标志物的分类。具有相同DE模式的生物标志物，可在下游通路富集分析中开展联合分析。当存在多种类型的转录本（transcript）时（如信使RNA [mRNA]、微小RNA [miRNA] 及长链非编码RNA [lncRNA] 等），可针对同一类别下的所有转录本，联合开展整合分析，包括miRNA/lncRNA靶基因富集分析以及miRNA-mRNA与lncRNA-mRNA因果调控网络分析。我们将所提方法应用于两例泛癌（Pan-cancer）转录组学研究实例，这些研究分别包含单一或多种类型的转录本。针对性下游分析成功鉴定出具备独特功能与调控关系的生物标志物类别，可为泛癌分析中的新假说构建提供启发。