Normalization, Subsampling, and Batch Handling

Overview

This vignette describes how PRIME handles normalization across libraries, subsampling for saturation analyses, and batch effects in multi-experiment CTSS datasets.

Assumes a CTSS RangedSummarizedExperiment object ctss is available; see vignette("03-ctss-processing") for how to build one.

Setup

library(PRIME)
library(SummarizedExperiment)

Size factor normalization

PRIME provides two size-factor-based normalization functions:

# Compute size factors (e.g., from total tags or an external method)
size_factors <- colData(ctss)$totalTags

# Normalize raw counts by size factors
ctss_norm <- PRIME::normalizeBySizeFactors(
    ctss,
    sizeFactors  = size_factors,
    inputAssay   = "counts",
    outputAssay  = "normalized"
)

# Normalize to TPM scaled by size factors
ctss_norm <- PRIME::TPMnormalizeBySizeFactors(
    ctss,
    sizeFactors  = size_factors,
    inputAssay   = "counts",
    outputAssay  = "normalizedTPM"
)

Subsampling

Subsampling is used to equalize library depth before comparative analyses and for sequencing saturation experiments.

Subsample to an absolute target depth

ctss_sub <- PRIME::subsampleTarget(ctss, target = 30e6)

Subsample to a proportion of the library

ctss_prop <- PRIME::subsampleProportion(ctss, proportion = 0.5)

Batch handling

When data are generated across multiple experimental batches, PRIME provides functions to assess and correct for batch effects:

# Assess support across batches
# (batch is a factor vector with one entry per sample)
batch_support <- PRIME::calcBatchSupport(
    ctss,
    batch        = colData(ctss)$Batch,
    inputAssay   = "counts",
    unexpressed  = 0
)

# Conditional normalization (normalize within batches)
ctss_cond <- PRIME::conditionalNormalize(
    ctss,
    batch        = colData(ctss)$Batch,
    inputAssay   = "counts",
    outputAssay  = "normalizedBatch"
)

Export normalized BigWig files

After normalization, export per-sample BigWig files for visualization or downstream tools:

PRIME::writeBw(
    ctss,
    replicates = colnames(ctss),
    dir        = "bw_output/"
)