Version Compatibility

Reference examples tested with: Rsamtools 2.18+, matplotlib 3.8+, numpy 1.26+, pyBigWig 0.3+, pysam 0.22+, samtools 1.19+

Before using code patterns, verify installed versions match. If versions differ:

• Python: pip show <package> then help(module.function) to check signatures
• R: packageVersion('<pkg>') then ?function_name to verify parameters
• CLI: <tool> --version then <tool> --help to confirm flags

If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.

Nucleosome Positioning

"Map nucleosome positions from ATAC-seq" → Separate nucleosome-free and mono-nucleosome fragments by size, then call nucleosome center positions and occupancy scores.

• CLI: nucleoatac run --bed peaks.bed --bam atac.bam --fasta ref.fa
• R: ATACseqQC::splitGAlignmentsByCut() for fragment separation

Extract nucleosome positions and occupancy from ATAC-seq fragment size patterns.

Background

ATAC-seq fragments reflect chromatin structure:

• < 100 bp: Nucleosome-free regions (NFR)
• 180-247 bp: Mono-nucleosome
• 315-473 bp: Di-nucleosome
• 558-615 bp: Tri-nucleosome

ATACseqQC (R)

Installation

BiocManager::install('ATACseqQC')

Fragment Size Distribution

library(ATACseqQC)
library(Rsamtools)

# Read BAM
bamfile <- 'sample.bam'

# Fragment size distribution
fragSize <- fragSizeDist(bamfile, 'sample')

# Nucleosome-free and mono-nucleosome ratios
# Automatic QC metrics

Nucleosome Positioning

Goal: Map nucleosome positions around TSS using ATAC-seq fragment size classes.

Approach: Read BAM, apply Tn5 shift correction, split fragments into NFR and mono-nucleosome classes by size, then compute signal profiles around TSS.

library(ATACseqQC)
library(TxDb.Hsapiens.UCSC.hg38.knownGene)
library(BSgenome.Hsapiens.UCSC.hg38)