Multi_Locus_View

Multi_Locus_View enables visualization, filtering, annotation, and integration of NGS-derived genomic loci across datasets to support data quality tracking, reproducibility, and biological interpretation.

Key Features:

• Multi-locus filtering and visualization: Filters and visualizes multiple genomic locations simultaneously to enable comparative locus-level analyses.
• Metadata-aware exploration and clustering: Examines metadata-labeled and clustered populations alongside detailed representations of individual elements.
• Cross-dataset signal integration: Integrates signals across multiple genomic datasets to reveal relationships between datasets and loci.
• Dimensionality reduction and clustering analysis: Performs dimensionality reduction and clustering on extracted signals to identify population structure and subgroups.
• Annotation for machine learning: Supports large-scale tagging and annotation of individual elements to generate labeled datasets for machine learning.

Scientific Applications:

• ChIP-seq analysis: Visualizes and compares ChIP-seq signal patterns across multiple loci and datasets to support interpretation of protein–DNA interactions.
• RNA-seq locus-level investigation: Enables locus-centric examination of RNA-seq-derived signals and associated metadata for transcriptomic studies.
• ATAC-seq chromatin accessibility studies: Integrates ATAC-seq signals across loci to assess chromatin accessibility patterns and population structure.

Methodology:

Processes NGS datasets using automated tools and pipelines to generate tabular outputs and static visualizations, transforms these outputs into interactive formats, extracts signals for dimensionality reduction and clustering, and produces visualizations of clustering.