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The rchime_options() function allows you to set vsearch specific optional parameters.

Source: R/rchime_options.R
rchime_options.Rd

The rchime_options() function allows you to set parameters for the various chimera detection functions. With the exception of dereplicate, we recommend using the defaults, unless you have a compelling reason to do otherwise.

Usage

rchime_options(
  processors = parallelly::availableCores(),
  dereplicate = TRUE,
  abskew = 2,
  minh = 0.28,
  mindiv = 0.8,
  xn = 8,
  dn = 1.4,
  maxp = 3
)

Arguments

processors

Integer, number of cores to use. Default = all available

dereplicate,

Boolean, The dereplicate option allows you to remove chimeras by sample. For example, if dereplicate parameter is FALSE, then if one group finds the sequence to be chimeric, it will be removed from all groups. If dereplicate is set to TRUE, sequences found to be chimeric are only removed from the sample they are found to be chimeric in. Default = TRUE.

abskew

Float, the minimum abundance skew (de novo only). Default = 2.0. abskew <- min (abund(parent1), abund(parent2)) / abund(query)

minh

Float, Mininum score to report chimera. Default 0.28. Values from 0.1 to 5 might be reasonable. Lower values increase sensitivity but may report more false positives. If you decrease –xn, you may need to increase –minh, and vice versa.

mindiv

Float, Minimum divergence ratio, default 0.8. Div ratio is 100%% %%identity between query sequence and the closest candidate for being a parent. If you don't care about very close chimeras, then you could increase –mindiv to, say, 1.0 or 2.0, and also decrease –min h, say to 0.1, to increase sensitivity. How well this works will depend on your data. Best is to tune parameters on a good benchmark.

xn

Float, Weight of a no vote, also called the beta parameter. Default 8.0. Decreasing this weight to around 3 or 4 may give better performance on denoised data.

dn

Float, Pseudo-count prior on number of no votes. Default 1.4. Probably no good reason to change this unless you can retune to a good benchmark for your data. Reasonable values are probably in the range from 0.2 to 2.

maxp

Integer, Maximum number of candidate parents to consider. Default 3.

Value

List containing selected rchime parameters and their values.

Author

Sarah Westcott, swestcot@umich.edu