TTCA: an R package for the identification of differentially expressed genes in time course microarray data

详细信息    查看全文

• 作者：Marco Albrecht ; Damian Stichel ; Benedikt Müller ; Ruth Merkle…
• 关键词：Differential expression ; Time series ; EGF ; Stimulation experiments ; Gene ontology ; Gene set analysis
• 刊名：BMC Bioinformatics
• 出版年：2017
• 出版时间：December 2017
• 年：2017
• 卷：18
• 期：1
• 全文大小：1380KB
• 刊物主题：Bioinformatics; Microarrays; Computational Biology/Bioinformatics; Computer Appl. in Life Sciences; Algorithms;
• 出版者：BioMed Central
• ISSN：1471-2105
• 卷排序：18

文摘

BackgroundThe analysis of microarray time series promises a deeper insight into the dynamics of the cellular response following stimulation. A common observation in this type of data is that some genes respond with quick, transient dynamics, while other genes change their expression slowly over time. The existing methods for detecting significant expression dynamics often fail when the expression dynamics show a large heterogeneity. Moreover, these methods often cannot cope with irregular and sparse measurements.