Version Compatibility

Reference examples tested with: bedtools 2.31+, matplotlib 3.8+, numpy 1.26+, pandas 2.2+, pyBigWig 0.3+, 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.

TF Footprinting

"Identify TF binding footprints in my ATAC-seq data" → Detect protected DNA regions within accessible chromatin where bound transcription factors block Tn5 insertion.

• CLI: TOBIAS ATACorrect → TOBIAS FootprintScores → TOBIAS BINDetect

TOBIAS Workflow

Goal: Identify transcription factor binding footprints within accessible chromatin regions.

Approach: Correct Tn5 insertion bias, compute per-base footprint scores, then detect bound/unbound TF motif sites using the three-step TOBIAS pipeline.

# 1. Correct Tn5 bias
tobias ATACorrect \
    --bam sample.bam \
    --genome genome.fa \
    --peaks peaks.bed \
    --outdir corrected/ \
    --cores 8

# 2. Calculate footprint scores
tobias FootprintScores \
    --signal corrected/sample_corrected.bw \
    --regions peaks.bed \
    --output footprints.bw \
    --cores 8

# 3. Bind TF motifs
tobias BINDetect \
    --motifs JASPAR_motifs.pfm \
    --signals footprints.bw \
    --genome genome.fa \
    --peaks peaks.bed \
    --outdir bindetect_output/ \
    --cores 8

TOBIAS Differential Footprinting

Goal: Compare TF binding between two conditions to identify regulators with differential activity.

Approach: Provide two bias-corrected signal tracks to BINDetect, which scores each motif site for differential binding between conditions.