Cropper

Cropper extracts significant peaks from Manhattan plots of genome-wide association studies (GWAS) to enable focused analysis and prioritization of genomic regions.

Key Features:

• Integration with Manhattan Harvester: Works in tandem with Manhattan Harvester for peak extraction from GWAS summary files.
• Automatic peak detection: Identifies genomic regions corresponding to peaks in Manhattan plots using algorithms from Manhattan Harvester.
• Quality scoring model: Applies a quality scoring system that evaluates peaks in a manner similar to human expert judgment.
• Batch processing: Processes large volumes of GWAS output files in batch mode to screen many datasets and phenotypes.
• Output generation: Produces graphical and numerical outputs summarizing detected plot regions for downstream analysis.

Scientific Applications:

• GWAS locus prioritization: Prioritizes candidate genomic regions and association peaks for follow-up studies in GWAS.
• Large-scale screening: Automates screening of many GWAS output files across multiple phenotypes to detect recurrent or novel association signals.
• Quantitative characterization: Facilitates quantitative and graphical characterization of association peaks derived from Manhattan plots and GWAS summary files.

Methodology:

Uses algorithms from Manhattan Harvester to identify peaks within GWAS summary files, applies a quality scoring model that mimics human expert judgment to those peaks, supports batch processing of GWAS output files, and generates graphical and numerical summaries of detected regions.