bio-atac-seq-differential-accessibility

What it does

Identify differentially accessible chromatin regions across conditions using DiffBind, csaw, DESeq2, or edgeR. Use when comparing ATAC-seq accessibility between treatment groups, choosing between consensus-peak vs sliding-window approaches, picking the correct normalization (full library vs reads-in-peaks), correcting batch with SVA/RUVseq, or interpreting log2FC and FDR thresholds in a chromatin context.

How it works

• Provides version compatibility notes and prerequisites for DiffBind, DESeq2, edgeR, csaw, limma, GenomicRanges, ChIPseeker, Subread, sva, RUVSeq.
• Describes multiple workflows: DiffBind on consensus peaks, csaw window-based analysis, or direct use of DESeq2/edgeR on peak-count data.
• Explains normalization and library-size options in DiffBind (normalize and library parameters), including defaults and alternative choices like RiP (reads-in-peaks) and spike-in strategies.
• Recommends peak strategy decisions based on experimental scenario (e.g., stable peaks vs shifting peak structure) and outlines an explicit decision tree for typical designs.
• Details a consensus peak-set strategy (intersection, union, majority, per-condition unions, iterative overlap) and notes the impact on FDR and interpretability.
• Outlines normalization schemes specific to ATAC-seq differential analysis, including DiffBind options (DBA_NORM_LIB, DBA_NORM_NATIVE, DBA_NORM_TMM, etc.), and when to apply each (e.g., background drift, global shifts).
• Provides failure modes and fixes for common tools (DiffBind library-size choices, summits parameter, csaw windowing, apeglm shrinkage, filterByExpr filtering in edgeR).
• Describes reconciliation steps when tools disagree and enables high-confidence reporting only when concordant across methods.
• Covers thresholds for effect size and significance, including FDR cutoffs and abs(log2FC) criteria, with conservative and exploratory guidelines.
• Includes sections on handling hidden batch effects with SVA/RUVseq and spike-in normalization, with R code patterns illustrating usage.

When to use it

• Use when comparing ATAC-seq accessibility between treatment groups or conditions.
• Use when deciding between consensus-peak and sliding-window approaches.
• Use when choosing between normalization strategies (full library vs reads-in-peaks) and when correcting batch effects with SVA/RUVseq.
• Use when interpreting log2FC and FDR thresholds in a chromatin context.

What it can touch

• DiffBind, csaw, DESeq2, edgeR, limma, DESeq2/edgeR backends, and associated normalization and batch-correction tools (sva, RUVSeq).
• Guidance references to spike-in normalization using exogenous chromatin (e.g., dm6 spike-ins) and peak-count matrices derived from Subread featureCounts.

Caveats

• Describes multiple tool-specific failure modes (e.g., DiffBind library-size confounding, summits parameter, csaw window sizing, apeglm shrinkage at low n, filtering with low counts).
• Recommends validating current consensus practices before locking pipelines; results can be sensitive to peak-set strategy and normalization choices.
• No outcomes are promised; instructions are descriptive of workflows, options, and caveats only.