pcot2

pcot2 assesses changes in multi-gene network activity using a permutation-based statistical framework that accounts for inter-gene correlation in two-sample comparisons.

Key Features:

• Permutation-Based Methodology: Uses permutation tests to assess the significance of changes in gene network activities.
• Inter-Gene Correlation Utilization: Incorporates inter-gene correlation information when evaluating network activity changes.
• Two-Sample Comparisons: Performs two-sample comparisons to detect differential network activity between conditions or groups.
• R Implementation: Implemented in the statistical programming language R.
• Bioconductor Integration: Distributed within the Bioconductor project with initial review and automated testing.

Scientific Applications:

• Genomics and Molecular Biology: Identifying how gene interactions and network activity change between biological conditions, such as disease versus healthy controls, using gene expression data.
• Gene Expression Network Analysis: Detecting altered multi-gene network activities to investigate regulatory mechanisms underlying biological processes.

Methodology:

Permutation testing that incorporates inter-gene correlation within a two-sample comparison framework; implemented in R and integrated with Bioconductor (initial review and automated testing).