TF-differential-binding
The TF-differential-binding pipeline performs differential transcription factor (TF) binding analysis from ChIP-seq datasets (TF peaks) using the DiffBind package in R. It identifies genomic regions where TF binding intensity significantly differs between experimental conditions (e.g., treatment vs. control, mutant vs. wild-type). Use the TF-differential-binding pipeline when you need to analyze the different function of the same TF across two or more biological conditions, cell types, or treatments using ChIP-seq data or TF binding peaks. This pipeline is ideal for studying regulatory mechanisms that underlie transcriptional differences or epigenetic responses to perturbations.
motif-scanning
This skill identifies the locations of known transcription factor (TF) binding motifs within genomic regions such as ChIP-seq or ATAC-seq peaks. It utilizes HOMER to search for specific sequence motifs defined by position-specific scoring matrices (PSSMs) from known motif databases. Use this skill when you need to detect the presence and precise genomic coordinates of known TF binding motifs within experimentally defined regions such as ChIP-seq or ATAC-seq peaks.
De-novo-motif-discovery
This skill identifies novel transcription factor binding motifs in the promoter regions of genes, or directly from genomic regions of interest such as ChIP-seq peaks, ATAC-seq accessible sites, or differentially acessible regions. It employs HOMER (Hypergeometric Optimization of Motif Enrichment) to detect both known and previously uncharacterized sequence motifs enriched within the supplied genomic intervals. Use the skill when you need to uncover sequence motifs enriched or want to know which TFs might regulate the target regions.