# Differential Expression Analysis with Long Read RNA-Seq Data
Software accompanying the paper *“Differential Expression Analysis with Long Read RNA-Seq Data”* by Liu Z., Song C., Wang Z., Fan Q., Yu J., Hao N., Chen S., Sun X., Ding H. (2026)
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## Overview
This R package implements a **hurdle negative binomial generalized linear model (hurdle-NB GLM)** for differential expression analysis of long-read RNA-Seq data. It provides:
- Data preparation and validation (`prepareDGE()`). Support for **matrix**, **data.frame**, **DGEList**, **DESeqDataSet**, or **SummarizedExperiment** inputs
- Estimation of **size factors** for normalization (`sizeFactorsEst()`)
- Estimation of **tag-wise dispersions** using emperical priors (`tagwiseEst()`)
- Gene-level differential expression testing using:
- **Likelihood Ratio Test** (`hurdle_LRT()`)
- **Wald Test** (`hurdle_Wald_Test()`)
The package is optimized for long-read sequencing data with high dropout rates, where zero inflation and overdispersion are common.
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## File Structure
| File / Folder | Description |
|---------------------------------------|-----------------------------------------------------------------------------|
| `R/estimateSizeFactors.R` | Functions for estimating normalization size factors for RNA-Seq counts. |
| `R/estimateDispersion.R` | Functions for prior estimation and tag-wise dispersion estimation. |
| `R/hurdleNBTest.R` | Functions for hurdle-NB differential expression testing (Wald & LRT). |
| `DESCRIPTION` | Package metadata, dependencies, and version information. |
| `NAMESPACE` | Exports, imports, and internal function definitions. |
| `README.md` | Package overview, usage, and installation instructions. |
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## Installation
To install the stable **release** version of `LRDE` from Bioconductor:
```r
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("LRDE")
```
To install the development version (currently required while under review):
```r
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("LRDE", version = "devel")
```
## Example usage
```r
# Load the package
library(LRDE)
# 1. Simulate a count matrix (negative binomial)
set.seed(123)
mat <- matrix(rnbinom(300, size = 5, mu = 5), nrow = 50)
grp <- factor(c("A", "A", "A", "B", "B", "B"))
# 2. Prepare the data object
y <- prepareDGE(mat, grp)
# 3. Estimate size factors for normalization
y <- sizeFactorsEst(y)
# 4. Estimate tag-wise gene dispersions
y <- tagwiseEst(y)
# 5a. Differential expression testing: Wald test
y <- hurdle_Wald_Test(y)
# 5b. Differential expression testing: Likelihood Ratio Test
y <- hurdle_LRT(y)
# 6. Access results
y$lrt_stats # LRT statistics per gene
y$wald_stats # Wald statistics per gene
y$p.values # Corresponding p-values
y$tagwise.disp # Estimated dispersions
y$zero_prob_matrix # Zero probabilities per group
```
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## Contact
For questions, comments, or collaborations, please contact:
- **Hongxu Ding** — <hongxuding@arizona.edu>
- **Ziyang Liu** — <ziyang773@arizona.edu>
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