ClusterPicker

Homer Annotation Data

This section displays the Homer annotation file you uploaded. Homer annotations provide genomic context for your features, including information about nearest genes, regulatory elements, and genomic regions.

What you'll see here:

• Raw annotation data as uploaded
• Genomic coordinates and feature annotations
• Gene assignments and regulatory element information
• Distance to nearest genes and annotation details

Welcome to ClusterPicker

ClusterPicker is a comprehensive tool for generating clustered heatmaps from high-throughput sequencing data. Whether you're working with RNA-seq, ATAC-seq, or other genomics datasets, ClusterPicker provides an intuitive interface for data visualization and cluster analysis.

How to Use ClusterPicker

1. Data Upload

Upload your count matrix with the first column containing feature names (gene symbols, ENSEMBL IDs for RNA-Seq, or peak IDs for ATAC-seq data). Subsequent columns should contain sample data with sample IDs as column headers.

2. Metadata Upload

Upload a CSV/TSV metadata file where:

• The first column can be row identifiers (or left blank)
• The second column should be named 'Sample' and contain all sample names same as present in the counts data
• Additional columns can contain treatment/condition information for heatmap annotations

3. Annotation (Optional)

For epigenomic assays, upload a Homer annotation files to add genomic context to your features. This is particularly useful for ATAC-seq peak analysis and provides additional annotation information.

4. Demo Data

New to ClusterPicker? Click 'Load Demo Data' to try the application with example datasets without uploading your own files.

Key Features

• Interactive Heatmaps: Generate publication-ready clustered heatmaps with customizable parameters
• Flexible Clustering: Extract specific gene/feature clusters from dendrograms
• Data Preview: Inspect your data before analysis with comprehensive preview tables
• Export Options: Download matrices, cluster assignments, and visualizations
• Multi-format Support: Accepts CSV, TSV, and TXT file formats

Supported Data Types

• RNA-seq: Gene expression matrices with gene symbols or ENSEMBL IDs
• ATAC-seq: Peak accessibility data with consensus peak features
• ChIP-seq: Peak intensity data from chromatin immunoprecipitation
• Other genomics data: Any count-based matrix data suitable for clustering analysis

Getting Started

Ready to begin? Navigate to the Heatmaps tab to start your analysis, or try our demo data to explore ClusterPicker's capabilities.