Convert filtered BAM files into RPM-normalized BigWig tracks.
npx skills add https://github.com/BIsnake2001/ChromSkills --skill track-generation
Please help me install this Agent Skill. Skill: track-generation Source: https://github.com/BIsnake2001/ChromSkills/tree/main/6.track-generation Command: npx skills add https://github.com/BIsnake2001/ChromSkills --skill track-generation
Converts filtered BAM files into browser-ready genome tracks (BigWig), enabling fast visualization and comparison across experiments.
Provide a filtered BAM file and let the tool generate RPM-normalized BigWig tracks for visualization.
High-intent search queries and answers about installing and using this skill.
You can generate RPM-normalized BigWig tracks directly from filtered BAM files. The process scales mapped reads to 1 million, applies chromosome size generation, and outputs browser-ready BigWig files for cross-sample comparison.
Yes, the workflow detects ATAC-seq inputs and automatically applies Tn5 offset correction during track creation. This adjustment is omitted for ChIP-seq, ensuring accurate signal representation for each assay type.
Yes, you can optionally visualize signal profiles around transcription start sites or user-defined target regions. This allows immediate QC inspection of the RPM-normalized BigWig tracks within your analysis environment.
RPM normalization scales mapped reads to reads per million, standardizing signal intensity across experiments. This allows fair cross-sample comparability when visualizing ATAC-seq or ChIP-seq genome tracks in a browser.
No, the track generation workflow automatically detects the genome assembly from your input data. It handles chromosome size generation internally, requiring only a filtered BAM file to produce the final BigWig output.
ChIP-seq tracks intentionally omit Tn5 offset correction, which is specific to ATAC-seq data. The workflow differentiates between the two assays, applying correction only when ATAC-seq is detected to ensure correct signal shifts.
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