Introduction to FracFixR

In FracFixR: Compositional Statistical Framework for RNA Fractionation Analysis

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Introduction

FracFixR is a compositional statistical framework for analyzing RNA-seq data from fractionation experiments. It addresses the fundamental challenge where library preparation and sequencing depth obscure the original proportions of RNA fractions.

This vignette demonstrates:

1. Basic usage with polysome profiling data
2. Differential proportion testing
3. Visualization of results
4. Advanced applications

Installation

# From CRAN
install.packages("FracFixR")

# From GitHub (development version)
devtools::install_github("Arnaroo/FracFixR")

Quick Start Example

Let's simulate a simple polysome profiling experiment:

library(FracFixR)

# Set seed for reproducibility
set.seed(123)

Creating Example Data

# Simulate count data for 500 genes across 12 samples
n_genes <- 100
n_samples <- 12

# Generate count matrix with varying expression levels
total_counts <- matrix(
  rnbinom(n_genes * 4, mu = 100, size = 10),
  nrow = n_genes,
  dimnames = list(
    paste0("Gene", 1:n_genes),
    paste0("Sample", 1:4)
  )
)
prob=c(1/4,1/4,1/2)

# distribute counts evenly accross different fractions in Control
multinom_samples <- apply(total_counts, c(1, 2), function(x) rmultinom(1, size = x, prob = prob))
reshaped <- aperm(multinom_samples, c(3, 2, 1))  # now (n, 4, 3)
reshaped_matrix1 <- matrix(reshaped, nrow = n_genes, ncol = 12)
colnames(reshaped_matrix1) <- paste0("V", rep(1:4, each = 3), "_p", 1:3)

counts<-cbind(total_counts[,1:2],reshaped_matrix1[,c(2:3,5:6)],total_counts[,3:4],reshaped_matrix1[,c(8:9,11:12)])

# Create annotation data frame
annotation <- data.frame(
  Sample = colnames(counts),
  Condition = rep(c("Control", "Treatment"), each = 6),
  Type = rep(c("Total", "Total", "Light_Polysome", "Heavy_Polysome","Light_Polysome", "Heavy_Polysome"), 2),
  Replicate = c("Rep1","Rep2", rep("Rep1", 2), rep("Rep2", 2), "Rep1","Rep2", rep("Rep1", 2), rep("Rep2", 2))
)

print(head(annotation))

Running FracFixR

# Run the main analysis
results <- FracFixR(MatrixCounts = counts, Annotation = annotation)

# View the structure of results
names(results)

Understanding the Output

The FracFixR output contains several components:

# 1. Fraction proportions for each replicate
print(results$Fractions)

# 2. Regression coefficients
print(results$Coefficients)

# 3. Estimated Proportions (first 5 genes, first 6 samples)
print(results$Propestimates[1:5, 1:6])

Visualizing Fraction Proportions

# Create fraction plot
frac_plot <- PlotFractions(results)
print(frac_plot)

The plot shows: - The proportion of RNA in each fraction - The "Lost" fraction (grey) representing unrecoverable material - Consistency across replicates

Differential Proportion Testing

Now let's identify genes with differential polysome association between conditions:

# Test for differential proportion in heavy polysomes
diff_heavy <- DiffPropTest(
  NormObject = results,
  Conditions = c("Control", "Treatment"),
  Types = "Heavy_Polysome",
  Test = "Logit"
)

# View top differentially associated genes
top_genes <- diff_heavy[order(diff_heavy$padj), ]
print(head(top_genes, 10))

Interpreting Results

• mean_diff: Difference in proportion between conditions
• log2FC: Log2 fold change of proportions
• padj: FDR-adjusted p-value

Positive mean_diff indicates higher proportion in Treatment.

Creating a Volcano Plot

volcano <- PlotComparison(
  diff_heavy,
  Conditions = c("Control", "Treatment"),
  Types = "Heavy_Polysome",
  cutoff = 20
)
print(volcano)

Data Requirements

For real experiments, ensure your data meets these requirements:

1. Count Matrix: Raw counts (not normalized)
2. Annotation: Must include:
3. Sample names matching count matrix columns
4. At least one "Total" sample per condition-replicate
5. Consistent fraction names across replicates

Session Info

sessionInfo()

References

Cleynen A, Ravindran A, Shirokikh N (2025). FracFixR: A compositional statistical framework for absolute proportion estimation between fractions in RNA sequencing data.

For more examples and advanced usage, see the FracFixR GitHub repository.

FracFixR documentation built on May 11, 2026, 9:09 a.m.