Statistics and Operation Research Department, University of Alicante, Spain.
Nucleic Acids Res. 2010 Jul;38(Web Server issue):W239-45. doi: 10.1093/nar/gkq488. Epub 2010 Jun 4.
Serial transcriptomics experiments investigate the dynamics of gene expression changes associated with a quantitative variable such as time or dosage. The statistical analysis of these data implies the study of global and gene-specific expression trends, the identification of significant serial changes, the comparison of expression profiles and the assessment of transcriptional changes in terms of cellular processes. We have created the SEA (Serial Expression Analysis) suite to provide a complete web-based resource for the analysis of serial transcriptomics data. SEA offers five different algorithms based on univariate, multivariate and functional profiling strategies framed within a user-friendly interface and a project-oriented architecture to facilitate the analysis of serial gene expression data sets from different perspectives. SEA is available at sea.bioinfo.cipf.es.
序贯转录组学实验研究与定量变量(如时间或剂量)相关的基因表达变化的动态。这些数据的统计分析意味着要研究全局和基因特异性表达趋势、识别显著的序贯变化、比较表达谱以及根据细胞过程评估转录变化。我们创建了 SEA(序贯表达分析)套件,为序贯转录组学数据的分析提供了一个完整的基于网络的资源。SEA 提供了基于单变量、多变量和功能分析策略的五种不同算法,这些算法都包含在用户友好的界面和面向项目的架构中,以从不同角度方便地分析序贯基因表达数据集。SEA 可在 sea.bioinfo.cipf.es 上获得。