PNGSeqR

PNGSeqR performs candidate gene selection from pooled next-generation sequencing (NGS) data using bulked segregant analysis (BSA).

Key Features:

• Input Compatibility: Accepts single-nucleotide polymorphism (SNP) markers from variant call format (VCF) files.
• BSA Algorithms: Implements four distinct bulked segregant analysis algorithms for genome-wide signal detection.
• Candidate Region Definition: Defines candidate genomic regions using permutation tests and fractile quantiles.
• Methodological Flexibility: Allows selection among analysis methods to match specific data and experimental designs.
• Differential Expression (DEG): Integrates differential expression gene analysis to identify genes with significant expression differences.
• Gene Ontology (GO): Performs GO analysis for functional annotation and prioritization of candidate genes.
• Visualization: Exports plots summarizing analysis results.

Scientific Applications:

• Genetic Mapping: Identifies candidate genes and genomic regions in mapping studies using pooled NGS and BSA.
• Gene Prioritization: Prioritizes genes associated with specific traits or diseases by integrating BSA with DEG and GO analyses.
• Breeding Programs: Supports mapping and candidate gene selection in plant and animal breeding programs.
• Human Genetics: Applies to mapping and candidate gene selection in human genetics studies.

Methodology:

Applies four BSA algorithms to SNPs from VCF files, uses permutation tests and fractile quantiles to define candidate regions, and integrates differential expression (DEG) and gene ontology (GO) analyses.