When should I use this skill in my workflow?

Use it when you need to validate TF binding specificity, identify potential co-factors within accessible chromatin regions, or generate motif-annotated BED files for visualization in genome browsers.

What does the Known Motif Scanning skill do?

This skill enables Claude to identify and map the precise locations of transcription factor (TF) binding motifs within genomic regions (like ChIP-seq or ATAC-seq peaks) using the HOMER software suite.

Can it scan for motifs across the entire genome?

Yes, the skill offers specialized modes for both region-specific scanning (e.g., within peak files) and genome-wide searches for potential binding sites.

What genomic file formats are supported?

The skill supports a wide range of inputs including BED, narrowPeak, and broadPeak files, as well as motif formats like HOMER, MEME, and TRANSFAC.

How does this skill improve bioinformatics productivity?

It automates tedious tasks such as chromosome name standardization (e.g., converting '1' to 'chr1'), motif format conversion from MEME to HOMER, and complex multi-step command-line execution for genomic scanning.

Known Motif Scanning

Name: Known Motif Scanning
Author: BIsnake2001

byBIsnake2001

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데이터 과학 및 ML

Identifies and maps transcription factor binding motifs within genomic regions like ChIP-seq and ATAC-seq peaks using HOMER.

소개

Automate the detection of specific transcription factor (TF) binding motifs within experimental genomic data to gain deeper insights into regulatory biology. This skill leverages HOMER to scan genomic regions for precise motif locations using position-specific scoring matrices, offering capabilities to search genome-wide, target specific peaks, or annotate existing datasets. It handles complex pre-processing tasks like chromosome name standardization and motif format conversion, providing researchers with standardized BED and TXT outputs for seamless integration into visualization tools and downstream analysis pipelines.

주요 기능

Supports multiple input formats including BED, narrowPeak, broadPeak, and HOMER peak files
2 GitHub stars
Generates motif-annotated BED files ready for genome browser visualization and feature analysis
Provides automated chromosome name standardization and motif format conversion from MEME to HOMER
Executes comprehensive motif scanning using HOMER for high-precision binding site detection
Offers specialized modes for region-specific scanning, genome-wide searching, and peak annotation

사용 사례

Identifying co-factor motif co-occurrence to infer cooperative binding mechanisms
Evaluating motif distribution patterns relative to transcription start sites or enhancers
Validating TF binding specificity within ChIP-seq or ATAC-seq peak regions

소개

주요 기능

Supports multiple input formats including BED, narrowPeak, broadPeak, and HOMER peak files
2 GitHub stars
Generates motif-annotated BED files ready for genome browser visualization and feature analysis
Provides automated chromosome name standardization and motif format conversion from MEME to HOMER
Executes comprehensive motif scanning using HOMER for high-precision binding site detection
Offers specialized modes for region-specific scanning, genome-wide searching, and peak annotation

사용 사례

Identifying co-factor motif co-occurrence to infer cooperative binding mechanisms
Evaluating motif distribution patterns relative to transcription start sites or enhancers
Validating TF binding specificity within ChIP-seq or ATAC-seq peak regions