Identification and prioritization of differentially expressed genes for time-series gene expression data
Identification and prioritization of differentially expressed genes for time-series gene expression data
复制标题
时间序列基因表达数据的差异表达基因的识别和优先级排序
DOI：
10.1007/s11704-016-6287-7
复制
发表时间：
2018
影响因子：
4.2
通讯作者：
Wang Chunyu
中科院分区：
文献类型：
--
作者：
Xing Linlin;Guo Maozu;Liu Xiaoyan;Wang Chunyu
Identification of differentially expressed genes (DEGs) in time course studies is very useful for understanding gene function, and can help determine key genes during specific stages of plant development. A few existing methods focus on the detection of DEGs within a single biological group, enabling to study temporal changes in gene expression. To utilize a rapidly increasing amount of single-group time-series expression data, we propose a two-step method that integrates the temporal characteristics of time-series data to obtain a B-spline curve fit. Firstly, a flat gene filter based on the Ljung–Box test is used to filter out flat genes. Then, a B-spline model is used to identify DEGs. For use in biological experiments, these DEGs should be screened, to determine their biological importance. To identify high-confidence promising DEGs for specific biological processes, we propose a novel gene prioritization approach based on the partner evaluation principle. This novel gene prioritization approach utilizes existing co-expression information to rank DEGs that are likely to be involved in a specific biological process/condition. The proposed method is validated on the Arabidopsis thaliana seed germination dataset and on the rice anther development expression dataset.
