ScanAFLP

ScanAFLP processes AFLP electropherograms to objectively select reproducible AFLP markers and improve phenotyping for population genetic analyses.

Key Features:

• Implementation: Implemented as an R script.
• Objective marker selection: Applies objective criteria based on peak height distribution and repeatability using blind controls to reduce subjective scoring bias.
• Error rate reduction: Lowers mismatch error rates compared with AFLPScore.
• Influence on genetic parameters: Application of selection criteria produced a 29% reduction in genetic diversity (HS) and an 8% increase in genetic differentiation (FST) relative to AFLPScore.
• Performance benchmarking: Evaluated against a large AFLP genome scan and compared with the AFLPScore method.

Scientific Applications:

• Population genetic studies: Produces consistent, reproducible AFLP data sets for estimates of genetic diversity and differentiation.
• Biological inference: Reduces genotype noise while preserving population genetic structure to support accurate inference.

Methodology:

Implements objective criteria based on peak height distribution and repeatability using blind controls; compared performance to AFLPScore on a large AFLP genome scan by assessing mismatch error rates and estimates of HS and FST; evaluated variance among replicates using random marker selections.