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Detect chimeras in your data.frames.

Source: R/rchime.R
rchime.data.frame.Rd

The rchime() function allows you to detect chimeras from your data using a de novo approach or alternatively a reference model.

Our preferred way of doing this is to use the abundant sequences as our reference (de novo).

This function uses code from the vsearch tools.

Usage

# S3 method for class 'data.frame'
rchime(
  data,
  reference = NULL,
  dereplicate = TRUE,
  verbose = TRUE,
  remove_chimeras = NULL,
  rchime_options = NULL,
  table_names = list(sequence_name = "sequence_name", sequence = "sequence", abundance =
    "abundance", sample = "sample")
)

Arguments

data

a data.frame containing your sequence data.

reference

a data.frame containing reference sequence data.

dereplicate

logical. The dereplicate option allows you to flag chimeras by sample. When dereplicate=FALSE, if a sequence is flagged as chimeric in one sample, it is removed from all samples. Our experience suggests that this is a bit aggressive since we’ve seen rare sequences get flagged as chimeric when they’re the most abundant sequence in another sample. For a more conservative approach, we recommend using the default dereplicate=TRUE which will only remove sequences from the samples in which they are flagged as chimeric.

verbose

logical, allow console outputs. Default = TRUE.

remove_chimeras

Only used when data is a strollur object.

rchime_options

List, You can fine tune the vsearch specific options using the [rchime_options()] function. Default = NULL.

table_names,

named list used to indicate the names of the columns in the data.frame. Only used when data is a data.frame. By default:

table_names <- list(sequence_name = "sequence_name", sequence = "sequence" abundance = "abundance", sample = "sample")

In table_names, 'sequence_name' is a string containing the name of the column in 'table' that contains the sequence names. Default column name is 'sequence_name'.

In table_names, 'sequence' is a string containing the name of the column in 'table' that contains the sequences. Default column name is 'sequence'.

In table_names, 'abundance' is a string containing the name of the column in 'table' that contains the abundances. Default column name is 'abundance'.

In table_names, 'sample' is a string containing the name of the column in 'table' that contains the samples. Default column name is 'sample'.

Value

list() containing a chimera report, and vector of the chimeric sequence's names. If running with multiple samples and dereplicate = TRUE, then a table containing the modified sequence abundances will also be returned.

References

Rognes T, Flouri T, Nichols B, Quince C, Mahé F. (2016) VSEARCH: a versatile open source tool for metagenomics. PeerJ 4:e2584. doi: 10.7717/peerj.2584

Edgar,R.C., Haas,B.J., Clemente,J.C., Quince,C. and Knight,R. (2011), UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 27:2194.

See also

rchime_options() to set vsearch specific parameters.

Author

Sarah Westcott, swestcot@umich.edu

Examples


# Detect chimeras from the dataset using de novo approach by sample
# (recommended)

data <- readRDS(rchime_example("miseq_data_frame_by_sample_small.rds"))

chimera_report <- rchime(data)
#> ℹ The de novo method runs with a single processor.
#> → rchime detected `128` chimeras in your dataset.
#> → It took `0.503028392791748` seconds to detect the chimeras.