removeBimeraDenovo: Remove bimeras from collections of unique sequences.
In dada2: Accurate, high-resolution sample inference from amplicon sequencing data

Description Usage Arguments Value See Also Examples

This function is a convenience interface for chimera removal. Two methods to identify chimeras are supported: Identification from pooled sequences (see isBimeraDenovo for details) and identification by consensus across samples (see isBimeraDenovoTable for details). Sequence variants identified as bimeric are removed, and a bimera-free collection of unique sequences is returned.

1	removeBimeraDenovo(unqs, method = "consensus", ..., verbose = FALSE)

`unqs`	(Required). A `uniques-vector` or any object that can be coerced into one with `getUniques`. A list of such objects can also be provided.
`method`	(Optional). Default is "consensus". Only has an effect if a sequence table is provided. If "pooled": The samples in the sequence table are all pooled together for bimera identification (`isBimeraDenovo`). If "consensus": The samples in a sequence table are independently checked for bimeras, and a consensus decision on each sequence variant is made (`isBimeraDenovoTable`). If "per-sample": The samples in a sequence table are independently checked for bimeras, and sequence variants are removed (zeroed-out) from samples independently (`isBimeraDenovo`).
`...`	(Optional). Arguments to be passed to `isBimeraDenovo` or `isBimeraDenovoTable`. The documentation of those methods detail the additional algorithmic parameters that can be adjusted.
`verbose`	(Optional). Default FALSE. Print verbose text output.

A uniques vector, or an object of matching class if a data.frame or sequence table is provided. A list of such objects is returned if a list of input unqs was provided.

isBimeraDenovoTable, isBimeraDenovo

derep1 = derepFastq(system.file("extdata", "sam1F.fastq.gz", package="dada2"))
dada1 <- dada(derep1, err=tperr1, errorEstimationFunction=loessErrfun, selfConsist=TRUE)
out.nobim <- removeBimeraDenovo(dada1)
out.nobim <- removeBimeraDenovo(dada1$clustering, method="pooled", minFoldParentOverAbundance = 2)