genomic-feature-annotation

To annotate genomic regions, you provide BED, narrowPeak, or broadPeak files alongside an explicit genome assembly and sample names. The Skill processes these inputs through Homer or ChIPseeker workflows to produce annotated region files and feature-distribution plots.

Yes, ChIPseeker mode provides an R-based annotation workflow for TF peak sets using TxDb and orgDb databases. It generates annotated region files, summary statistics, and visualization plots to help interpret regulatory landscapes.

Genomic annotation supports BED, narrowPeak, and broadPeak input formats across various species. You must explicitly specify the genome assembly, input region files, and sample naming to ensure reproducible results.

Annotating genomic regions with gene-based features is the best way to identify TF target genes. By processing peak sets through Homer or ChIPseeker, you get annotated region files and feature-distribution visuals for interpreting regulatory landscapes.

Yes, Homer mode uses annotatePeaks.pl with customizable options, and generating reproducible results requires explicit genome assembly, input region files, sample naming, and optional Homer annotation settings.

Explicit sample naming is required alongside input region files and genome assembly to enable reproducible results. It ensures annotated output files and visualization plots are correctly tracked across Homer or ChIPseeker workflows.