FAMD

FAMD analyzes multilocus, fragment-based (dominant) fingerprinting data (e.g., RAPD, AFLP) and assesses the effects of missing band presence-absence data by using random assignment to support diversity and distance-based analyses.

Key Features:

• Missing data handling: Performs random assignment of band presence-absence for missing entries to explore alternative assumptions about incomplete fingerprinting datasets.
• Pairwise similarity and Shannon's index: Computes pairwise similarity coefficients and Shannon's index to quantify genetic similarity and diversity.
• Visualization of missing data effects: Reports minimum, maximum, and average similarity coefficients to visualize how missing values influence tree structures and comparative analyses.
• Range reporting: Indicates ranges of analytical outcomes across random assignments to inform interpretation of results under different missing-data scenarios.
• Distance-based and phylogenetic analyses: Supports distance-based analysis, bootstrapping, and consensus tree generation for comparative and phylogenetic inference.
• Population genetics analyses: Performs allele frequency estimation, AMOVA (Analysis of Molecular Variance), and inter-population distance calculations.
• Data types supported: Designed for multilocus, fragment-based dominant fingerprinting data such as RAPD and AFLP.

Scientific Applications:

• Dominant fingerprint analysis: Analysis of RAPD and AFLP datasets to assess genetic diversity and structure while accounting for missing data.
• Missing-data impact assessment: Evaluation of how scattered or grouped missing values affect similarity metrics, tree topology, and downstream interpretations.
• Population genetics studies: Estimation of allele frequencies, AMOVA, and inter-population distances for population-structure and diversity investigations.
• Phylogenetic and comparative inference: Generation of distance matrices, bootstrapped support, and consensus trees for comparative analyses of samples profiled by dominant markers.

Methodology:

Random assignment of band presence-absence for missing data; calculation of pairwise similarity coefficients and Shannon's index; computation of minimum, maximum, and average similarity values across randomizations; distance-based analyses with bootstrapping and consensus tree generation; allele frequency estimation, AMOVA, and inter-population distance calculations.