Biscap and cfdr

Biscap and cfdr improve the accuracy of sequence alignment and single nucleotide polymorphism (SNP) calling by combining BiSCaP (Binomial SNP Calling from Probabilities) and cFDR (comparative False Discovery Rate) for comparative and population genomic analyses.

Key Features:

• BiSCaP (Binomial SNP Calling from Probabilities): Determines homozygous and heterozygous positions within sequence alignments using binomial probability calculations based on an expected error rate to classify true SNPs versus sequencing errors.
• cFDR (comparative False Discovery Rate): Evaluates and benchmarks the accuracy of input read datasets, alignments, and SNP-calling strategies by comparing false discovery rates, particularly when an isolate has a corresponding or closely related reference sequence.
• Validation: Performance has been benchmarked against other SNP callers using three fungal genomes and reported high accuracy.

Scientific Applications:

• Comparative Genomics: Supports comparison of genetic variation across species or isolates by providing probabilistic SNP calls and alignment accuracy metrics.
• Population Genomics: Aids identification of population-specific variants by distinguishing homozygous and heterozygous positions with error-aware probability models.
• Benchmarking and Method Selection: Enables evaluation and selection of alignment and SNP-calling methods for specific datasets via comparative false discovery rate assessment.

Methodology:

BiSCaP applies binomial probability calculations using an expected sequencing error rate to estimate the likelihood that nucleotide variations are true SNPs versus errors; cFDR computes and compares false discovery rates across read datasets, alignments, and SNP-calling strategies, with benchmarking performed using three fungal genomes.