bam-to-bigwig-conversion

BAM-to-BigWig conversion

Summary

Convert bias-corrected ATAC-seq signal data from BAM format to BigWig format for visualization and downstream footprinting analysis. This transformation enables efficient storage, scalable genome browser display, and preparation for footprint scoring.

When to use

After running TOBIAS ATACorrect to generate bias-corrected signal tracks from aligned ATAC-seq reads. Use this skill when you have corrected cutsite signal (as .bw or equivalent intermediate format) that must be visualized across the genome or fed into footprint scoring tools like ScoreBigwig.

When NOT to use

• Input is already in BigWig format—no conversion needed.
• Analysis goal is to call peaks or identify open chromatin regions; use peak-calling tools (e.g., MACS2) directly on aligned BAM instead.
• Working with raw, uncorrected ATAC-seq cutsite data for motif discovery without bias correction; apply ATACorrect first.

Inputs

• Bias-corrected ATAC-seq signal data (as .bw output from TOBIAS ATACorrect, or intermediate cutsite BAM/bedGraph)
• Reference genome index or chrom.sizes file (for bedGraph-to-bigWig conversion if needed)

Outputs

• BigWig (.bw) file containing bias-corrected signal track
• IGV/genome-browser compatible signal visualization

How to apply

Following TOBIAS ATACorrect bias correction, the corrected signal output (stored initially as a bigWig file by ATACorrect itself) is ready for visualization and downstream analysis. ATACorrect natively outputs bias-corrected signal as a .bw file alongside uncorrected, bias model, and expected signal tracks. No additional conversion step is strictly required—ATACorrect produces the BigWig directly. However, if working with intermediate cutsite signals or custom corrected BAM files, conversion to BigWig can be achieved through standard genomic tools (e.g., bedtools, deeptools, or UCSC tools) that bin aligned reads into fixed-width windows and store normalized signal values. The resulting BigWig tracks preserve positional cutsite resolution while enabling rapid querying by genome browsers and footprinting downstream tools.