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nexodiff: RNA-seq Differential Expression Analysis

nexodiff is an R package for performing differential expression analysis on RNA-seq data. It provides a flexible, object-oriented framework for analyzing, visualizing, and interpreting gene expression data from complex experimental designs.

The package is built around a series of R6 classes that guide the user through the analysis pipeline, from reading annotation and design files to performing statistical analysis and generating plots.

Workflow Overview

The typical analysis workflow follows these steps:

  1. Setup: Define the experimental layout with a PairwiseDesign object and load gene/transcript information with an Annotation object.
  2. Data Handling: Import transcript-level abundances (e.g., from Kallisto) into an ExprDataTranscript object. This data can then be normalized, filtered, and summarized into gene-level counts in an ExprDataGene object.
  3. Analysis: Use an analysis class like PairwiseDESeq2 to perform differential expression testing on the gene-level data. The results can be explored through various plotting functions (MA plots, volcano plots, heatmaps) and exported.
schema
schema

Installation

You can install the development version of nexodiff from GitHub with:

# install.packages("devtools")
devtools::install_github("nexomis/nexodiff")

Testing

See TESTING.md for detailed testing instructions, including how to run tests, generate coverage reports, and visualize results with Allure.

Continuous Integration

Tests run automatically on: - Push events to main and master branches - Pull requests - Releases

R-CMD-check

Getting Started

For a detailed guide and practical examples, please see the “Examples” vignette included with the package.