nRCFV_Reader

nRCFV_Reader quantifies compositional heterogeneity in nucleotide and amino acid datasets by calculating Relative Composition Frequency Variability (RCFV) and normalized RCFV (nRCFV) to assess variability that can produce phylogenetic artefacts.

Key Features:

• Quantification of compositional heterogeneity: Calculates RCFV and nRCFV metrics to measure variability in nucleotide and amino acid composition across datasets.
• Bias correction in nRCFV: Normalizes RCFV to correct biases arising from sequence length, number of taxa, and number of possible character states, yielding assessments independent of dataset size.
• Robustness to missing data: RCFV and nRCFV metrics maintain performance and provide consistent measurements in the presence of incomplete data.

Scientific Applications:

• Phylogenetic analysis: Identifies compositional heterogeneity that can generate phylogenetic artefacts prior to tree reconstruction.
• Data quality assessment: Evaluates compositional bias in genomic and proteomic datasets to inform downstream analyses.

Methodology:

Computes RCFV and normalized RCFV (nRCFV) to evaluate nucleotide or amino acid composition variability across a dataset; implementation provided in R.