atac-seq-signal-normalization

atac-seq-signal-normalization

Summary

Correct ATAC-seq signal for Tn5 transposase insertion bias to enable accurate detection of transcription factor footprints. This skill applies the TOBIAS ATACorrect module to model and remove sequence-dependent insertion preferences, producing bias-corrected signal tracks suitable for footprinting analysis.

When to use

Apply this skill when you have aligned ATAC-seq BAM files and need to detect transcription factor binding sites via footprint analysis. The skill is essential because raw Tn5 insertion signal contains systematic bias toward certain DNA sequences; correction is necessary before scoring footprints (depletion patterns around protein-bound regions) or comparing signal across genomic regions with different sequence composition.

When NOT to use

• Input is already a bias-corrected signal track or normalized feature table — do not apply correction twice.
• ATAC-seq data lacks sufficient depth or quality (e.g. <10M unique fragments) — bias modeling will be unreliable.
• Analysis does not require footprint-level resolution — for broad chromatin accessibility assessment, bias correction may not be necessary.

Inputs

• Aligned ATAC-seq reads (BAM format)
• Reference genome sequence (FASTA format)
• Open chromatin peak regions (BED format)

Outputs

• Uncorrected cutsite signal (bigWig)
• Tn5 insertion bias model (bigWig)
• Expected bias-corrected signal (bigWig)
• Bias-corrected cutsite signal (bigWig)
• ATACorrect diagnostic plots (PDF)

How to apply

Load aligned ATAC-seq BAM file, corresponding reference genome FASTA, and peak regions (BED format) into TOBIAS ATACorrect. The tool models the sequence preference of Tn5 transposase by examining the nucleotide context of insertion sites within open chromatin peaks, then applies this bias model to normalize the cutsite signal genome-wide. ATACorrect outputs both the bias model (as a bigWig track) and the bias-corrected signal; the corrected signal should show reduced spurious variation driven by sequence composition and enhanced visibility of footprints (insertional depletion around transcription factor binding sites). Evaluate success by visual inspection of corrected signal in genome browsers and comparison of footprint clarity before and after correction.