PacBioErrfun: Estimate error rates from transition counts in PacBio CCS...

In benjjneb/dada2: Accurate, high-resolution sample inference from amplicon sequencing data

Estimate error rates from transition counts in PacBio CCS data.

Description

This function accepts a matrix of observed transitions from PacBio CCS amplicon sequencing data, with each transition corresponding to a row (eg. row 2 = A->C) and each column to a quality score (eg. col 31 = Q30). It returns a matrix of estimated error rates of the same shape. Error rates are estimates by loessErrfun for quality scores 0-92, and individually by the maximum likelihood estimate for the maximum quality score of 93.

Usage

PacBioErrfun(trans)

Arguments

trans

(Required). A matrix of the observed transition counts. Must be 16 rows, with the rows named "A2A", "A2C", ...

Value

A numeric matrix with 16 rows and the same number of columns as trans. The estimated error rates for each transition (row, eg. "A2C") and quality score (column, eg. 31), as determined by loess smoothing over the quality scores within each transition category.

Examples

derep.PB <- derepFastq(system.file("extdata", "samPB.fastq.gz", package="dada2"))
dada.PB <- dada(derep.PB, errorEstimationFunction=PacBioErrfun, BAND_SIZE=32, selfConsist=TRUE)
err.PB <- PacBioErrfun(dada.PB$trans)

benjjneb/dada2 documentation built on Feb. 1, 2024, 10:50 p.m.