frogs_normalisation

frogs_normalisation performs normalization of high-throughput (next-generation) DNA sequencing datasets by equalizing sample element counts via random sampling to mitigate sequencing-depth biases for comparative analyses.

Key Features:

• Random Sampling Normalization: Equalizes the number of elements (e.g., reads or genes) per sample using random sampling to reduce biases introduced by varying sequencing depths.
• Galaxy Project Integration: Integrates with the Galaxy Project framework to enable execution within Galaxy workflows and use of Galaxy infrastructure.
• Provenance Tracking: Leverages Galaxy's provenance recording to capture procedural details for inspection, publication, and reuse.

Scientific Applications:

• Differential Gene Expression Analysis: Provides normalized sample counts suitable for downstream differential gene expression workflows.
• Comparative Analyses of High-Throughput Sequencing Data: Mitigates sequencing-depth-driven technical variability in biomedical and other sequencing-based comparative studies.

Methodology:

Performs random subsampling to equalize element counts (e.g., reads or genes) across samples and records execution provenance within the Galaxy framework.