Description
Score how strongly each per-read-length metagene profile shows the 3-nucleotide periodicity expected of actively translating ribosomes. For each candidate (read length, P-site offset) pair, Rp-Bp fits two competing Bayesian models to the count window around annotated start codons: a "periodic" model whose signal repeats every three nucleotides, and a "non-periodic" background model. The Bayes factor (ratio of the two marginal likelihoods) quantifies how much the data prefer the periodic explanation.
Returns one row per (length, offset) pair with the mean and variance of
the log Bayes factor across MCMC samples. Downstream,
rpbp/selectperiodicoffsets picks the best offset per length from
this table, and rpbp/getperiodiclengthsoffsets filters to the
high-confidence pairs that drive ORF-level scoring.
Uses the Stan models bundled inside the rpbp Python package.
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