loessErrfun: Use a loess fit to estimate error rates from transition...
In dada2: Accurate, high-resolution sample inference from amplicon sequencing data
Description
Usage
Arguments
Value
Examples
Description
This function accepts a matrix of observed transitions, 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 a loess fit
of the observed rates of each transition as a function of the quality score.
Self-transitions (i.e. A->A) are taken to be the left-over probability.
Usage
1
loessErrfun(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
1
2
3
derep1 <- derepFastq(system.file("extdata", "sam1F.fastq.gz", package="dada2"))
dada1 <- dada(derep1, err=tperr1)
err.new <- loessErrfun(dada1$trans)
dada2 documentation built on Nov. 8, 2020, 6:48 p.m.
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Description Usage Arguments Value Examples
Description
This function accepts a matrix of observed transitions, with each transition
corresponding to a row (eg. row 2 = A->C) and each column to a quality score
(eg. col 31 = Q30). It returns a matrix of estimated error
rates of the same shape. Error rates are estimates by a loess fit
of the observed rates of each transition as a function of the quality score.
Self-transitions (i.e. A->A) are taken to be the left-over probability.
Usage
1 | loessErrfun(trans)
|
Arguments
trans |
(Required). A matrix of the observed transition counts. Must be 16 rows, with the rows named "A2A", "A2C", ... |
Value
A numeric matrix with 16 rows and the same number of columns as trans.
The estimated error rates for each transition (row, eg. "A2C") and quality score
(column, eg. 31), as determined by loess smoothing over the quality
scores within each transition category.
Examples
1 2 3 | derep1 <- derepFastq(system.file("extdata", "sam1F.fastq.gz", package="dada2"))
dada1 <- dada(derep1, err=tperr1)
err.new <- loessErrfun(dada1$trans)
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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