SparK

SparK generates publication-quality vector graphics from next-generation sequencing (NGS) tracks to visualize genomic data such as RNA-seq, ChIP-seq, and ATAC-seq and to represent replicate variability and statistical summaries.

Key Features:

• Auto-Generation of SVG Figures: Automatically produces true vector graphic (SVG) figures directly from NGS-based tracks including RNA-seq, ChIP-seq, and ATAC-seq.
• Customization of Tracks: Provides programmatic control to modify track appearance, adjust genomic regions, add or remove tracks, and overlay replicate datasets.
• Replicate Statistics: Computes and plots averaged replicate signals and standard deviation tracks to visualize variability across replicates.
• Highlighting Significant Regions: Highlights genomic regions with significant changes in signal on the generated plots.
• Implementation: Implemented in Python 3 and outputs true SVG vector graphics suitable for publication.

Scientific Applications:

• Genomics: Visualizing genome-wide coverage and signal tracks from NGS experiments such as RNA-seq, ChIP-seq, and ATAC-seq.
• Transcriptomics: Presenting RNA-seq signal profiles and replicate variability at gene or transcript loci.
• Epigenetics: Displaying ChIP-seq profiles and epigenetic modification signals with integrated statistical summaries.
• Chromatin Accessibility: Depicting ATAC-seq peaks and accessibility with averaged replicates and variability metrics.
• Figure Preparation: Producing publication-ready visualizations that represent complex NGS datasets and replicate statistics.

Methodology:

Automates generation of SVG figures from NGS tracks using Python 3, computing averaged replicate signals and standard deviation tracks and annotating regions with significant changes.