removeBimeraDenovo {dada2} | R Documentation

## Remove bimeras from collections of unique sequences.

### Description

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.

### Usage

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

### Arguments

`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.

### Value

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.

### See Also

`isBimeraDenovoTable`, `isBimeraDenovo`

### Examples

    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)

[Package dada2 version 1.8.0 Index]