maSigPro

maSigPro identifies genes with significant differential expression profiles across experimental groups in time-course studies using microarray and RNA-Seq datasets.

Key Features:

• Time-Course Analysis: Detects temporal changes in gene expression across multiple time points.
• Regression-Based Approach: Uses regression models to compare expression profiles between experimental groups.
• Support for RNA-Seq Data: Extends to count-based RNA-Seq by incorporating generalized linear models (GLMs) for appropriate modeling of counts.
• Microarray Compatibility: Retains support for microarray expression data and associated analysis workflows.
• Integration with R and Bioconductor: Implemented as an R package interoperable with Bioconductor data structures and analysis pipelines.
• Performance Validation: maSigPro-GLM has been evaluated on simulated time-course scenarios and real experimental datasets.

Scientific Applications:

• Developmental Biology: Characterizes temporal gene expression changes during organismal development.
• Cancer Research: Analyzes time-dependent transcriptional responses to treatments or disease progression in cancer studies.
• Systems Biology: Investigates temporal behavior of regulatory networks and dynamic systems-level responses.

Methodology:

Fitting regression models to time-course data to identify genes with differing expression profiles between groups, and applying generalized linear models (GLMs) to model RNA-Seq count data.