The Key Laboratory of Advanced Interdisciplinary Studies, The First Affiliated Hospital of Guangzhou Medical University, GMU-GIBH Joint School of Life Sciences, The Guangdong-Hong Kong-Macao Joint Laboratory for Cell Fate Regulation and Diseases, Guangzhou Medical University, Guangzhou 510182, People's Republic of China.
School of Zoology, The George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 6997801, Israel.
Bioinformatics. 2024 Aug 2;40(8). doi: 10.1093/bioinformatics/btae507.
High-throughput technologies yield a broad spectrum of multi-omics datasets, which offer unparalleled insights into complex biological systems. However, effectively analyzing this diverse array of data presents challenges, considering factors such as species diversity, data types, costs, and limitations of the available tools.
Herein, we present ExpOmics, a comprehensive web platform featuring 7 applications and 4 toolkits, with 28 customizable analysis functions spanning various analyses of differential expression, co-expression, Weighted Gene Co-expression Network Analysis (WGCNA), feature selection, and functional enrichment. ExpOmics allows users to upload and explore multi-omics data without organism restrictions, supporting various expression data, including genes, mRNAs, lncRNAs, miRNAs, circRNAs, piRNAs, and proteins and is compatible with diverse gene nomenclatures and expression values. Moreover, ExpOmics enables users to analyze 22 427 transcriptomic datasets of 196 cancer subtypes sourced from 63 projects of The Cancer Genome Atlas Program (TCGA) to identify cancer biomarkers. The analysis results from ExpOmics are presented in high-quality graphical formats suitable for publication and are available for free download. A case study using ExpOmics identified two potential oncogenes, SERPINE1 and SLC43A1, that may regulate colorectal cancer through distinct biological processes. In summary, ExpOmics can serves as a robust platform for global researchers to explore multi-omics data, gain biological insights, and formulate testable hypotheses.
ExpOmics is available at http://www.biomedical-web.com/expomics.
高通量技术产生了广泛的多组学数据集,为复杂的生物系统提供了前所未有的洞察力。然而,考虑到物种多样性、数据类型、成本和可用工具的限制等因素,有效地分析这种多样化的数据具有一定的挑战性。
在此,我们介绍了 ExpOmics,这是一个全面的网络平台,具有 7 个应用程序和 4 个工具包,具有 28 个可定制的分析功能,涵盖了差异表达、共表达、加权基因共表达网络分析(WGCNA)、特征选择和功能富集等各种分析。ExpOmics 允许用户上传和探索多组学数据,不受生物体限制,支持各种表达数据,包括基因、mRNA、lncRNA、miRNA、circRNA、piRNA 和蛋白质,并且与各种基因命名法和表达值兼容。此外,ExpOmics 允许用户分析来自 63 个癌症基因组图谱计划(TCGA)项目的 196 种癌症亚型的 22427 个转录组数据集,以鉴定癌症生物标志物。ExpOmics 的分析结果以高质量的图形格式呈现,适合发表,并可免费下载。使用 ExpOmics 的案例研究确定了两个潜在的癌基因 SERPINE1 和 SLC43A1,它们可能通过不同的生物学过程调节结直肠癌。总之,ExpOmics 可以作为一个强大的平台,供全球研究人员探索多组学数据,获得生物学见解,并提出可测试的假设。
ExpOmics 可在 http://www.biomedical-web.com/expomics 上获得。