Next maSigPro: updating maSigPro bioconductor package for RNA-seq time series
By María José Nueda, Sonia Tarazona, Ana Conesa. Bioinform., 2014
331 citations recorded by the source corpus.
Motivation: 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. Results: 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. Availability and implementation: The package is freely available under the LGPL license from the Bioconductor Web site (http://bioconductor.org). Contact: mj.nueda@ua.es or aconesa@cipf.es
Subfields: Molecular Biology
View Paper: https://www.semanticscholar.org/paper/7262866140d22894d5f9566fbc162648479971ed
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In Molecular Biology
- Sonia Tarazona
- Ana Conesa
- Laura L. Elo
- Sandrine Dudoit
- Xuegong Zhang
- Lieven Clement
- K. Van den Berge
- David Gomez-Cabrero
Citations in the corpus
- A survey of best practices for RNA-seq data analysis (2016, methodology): “…expression tools can only perform a pair-wise comparison, others such as edgeR [57], limma-voom [55], DESeq [48], DESeq2 [58], and maSigPro [213] can perform multiple comparisons, include different covariates or analyze time-series data. of biological interest to assess whether particular…”
- Trajectory-based differential expression analysis for single-cell sequencing data (2019, methodology): “A number of methods have been developed for the analysis of bulk RNA-seq time-series data, which can exploit the temporal resolution of samples assayed at different times 8 – 10 .”