Nueda María José, Tarazona Sonia, Conesa Ana
Statistics and Operational Research Department, University of Alicante, 03690, Alicante, Spain, Genomics of Gene Expression Laboratory, Prince Felipe Research Centre, 46012 Valencia, Spain and Applied Statistics, Operational Research and Quality Department, Polytechnic University of Valencia, 46020 Valencia, Spain.
Statistics and Operational Research Department, University of Alicante, 03690, Alicante, Spain, Genomics of Gene Expression Laboratory, Prince Felipe Research Centre, 46012 Valencia, Spain and Applied Statistics, Operational Research and Quality Department, Polytechnic University of Valencia, 46020 Valencia, Spain Statistics and Operational Research Department, University of Alicante, 03690, Alicante, Spain, Genomics of Gene Expression Laboratory, Prince Felipe Research Centre, 46012 Valencia, Spain and Applied Statistics, Operational Research and Quality Department, Polytechnic University of Valencia, 46020 Valencia, Spain.
Bioinformatics. 2014 Sep 15;30(18):2598-602. doi: 10.1093/bioinformatics/btu333. Epub 2014 Jun 3.
The widespread adoption of RNA-seq to quantitatively measure gene expression has increased the scope of sequencing experimental designs to include time-course experiments. maSigPro is an R package specifically suited for the analysis of time-course gene expression data, which was developed originally for microarrays and hence was limited in its application to count data.
We have updated maSigPro to support RNA-seq time series analysis by introducing generalized linear models in the algorithm to support the modeling of count data while maintaining the traditional functionalities of the package. We show a good performance of the maSigPro-GLM method in several simulated time-course scenarios and in a real experimental dataset.
The package is freely available under the LGPL license from the Bioconductor Web site (http://bioconductor.org).
RNA测序被广泛用于定量测量基因表达,这扩大了测序实验设计的范围,使其包括时间进程实验。maSigPro是一个专门用于分析时间进程基因表达数据的R包,它最初是为微阵列开发的,因此在应用于计数数据时受到限制。
我们对maSigPro进行了更新,通过在算法中引入广义线性模型来支持计数数据建模,同时保留该包的传统功能,以支持RNA测序时间序列分析。我们在几个模拟的时间进程场景和一个真实实验数据集中展示了maSigPro-GLM方法的良好性能。
该包可在LGPL许可下从Bioconductor网站(http://bioconductor.org)免费获取。