denoise_then_cluster_no_primer_pooled.md

denoise-then-cluster-no-primer-pooled: Denoise valid data into ZOTUs, then cluster them into OTUs at the user's defined identity using the uniose3 and uclust algorithm

Command Line Interface

Usage: qiime usearch denoise-then-cluster-no-primer-pooled 
           [OPTIONS]

  This Method Pools All Samples Together, then Extracts Biological Reads Using
  the Unoise3 Algorithm, Finally OTUs are Generated by Clustering zOTUs Using
  the Uclust Algorithm at the user's defined identity threshold. Non-Biological
  Sequence (i.e. Barcodes, Primers) MUST be REMOVED Prior to this step. You
  MUST Also MERGE Your Reads If You are Using PAIRED-END Sequncing Protocol.
  You Can Directly Use the 'Valid-Data' Provided by the Sequencing Center.
  Vsearch was supported in early development but became deprecated for shipment.

Inputs:
  --i-demultiplexed-sequences ARTIFACT SampleData[SequencesWithQuality] |
    SampleData[JoinedSequencesWithQuality]
                         Quality screened, Adapter stripped,
                         Joined(paired-end) sequences.              [required]
Parameters:
  --p-trim-left INTEGER  Position at which sequences should be trimmed due to
    Range(0, None)       low quality. This trims the 5' end of the of the
                         input sequences.                         [default: 0]
  --p-trunc-len INTEGER  Position at which sequences should be truncated due
    Range(0, None)       to decrease in quality. This truncates the 3' end of
                         the of the input sequences. Reads that
                         are shorter than this value will be discarded. If 0
                         is provided, no truncation or length filtering will
                         be performed                             [default: 0]
  --p-min-len INTEGER    Reads with less length than this number value will
    Range(0, None)       be discarded.                           [default: 50]
  --p-max-ee NUMBER      Reads with number of expected errors higher than
    Range(0.0, None)     this value will be discarded.          [default: 1.0]
  --p-perc-identity PROPORTION
    Range(0.0, 1.0)      The identity threshold used for OTU clustering.
                                                               [default: 0.99]
  --p-n-threads VALUE Int % Range(1, None) | Str % Choices('auto')
                         The number of threads to use for computation. If set
                         to auto, the plug-in will use (all vcores - 3)
                         present on the node.                [default: 'auto']
  --p-min-size INTEGER   The minimum abundance of input reads to be retained.
    Range(1, None)       For higher sensivity, reducing minsize to 4 is
                         reasonable. Note: with smaller minsize, there tends
                         to be more errors in low-abundance zotus.
                                                                  [default: 8]
  --p-unoise-alpha NUMBER
    Range(0.0, None)     See UNOISE2 paper for definition       [default: 2.0]
  --p-use-vsearch / --p-no-use-vsearch
                         Use vsearch instead of usearch for computation .
                                                              [default: False]
Outputs:
  --o-table ARTIFACT FeatureTable[Frequency]
                         The resulting feature table.               [required]
  --o-representative-sequences ARTIFACT FeatureData[Sequence]
                         The resulting feature sequences. Each feature in the
                         feature table will be represented by exactly one
                         sequence.                                  [required]
  --o-stats ARTIFACT SampleData[USEARCHStats]
                         DataFrame containing statistics during each step of
                         the pipeline.                              [required]
Miscellaneous:
  --output-dir PATH      Output unspecified results to a directory
  --verbose / --quiet    Display verbose output to stdout and/or stderr
                         during execution of this action. Or silence output if
                         execution is successful (silence is golden).
  --example-data PATH    Write example data and exit.
  --citations            Show citations and exit.
  --help                 Show this message and exit.

Artifact API

Import

from qiime2.plugins.usearch.methods import denoise_then_cluster_no_primer_pooled

Example Usage

zotu_tab, zotus, unoise_stats, = denoise_then_cluster_no_primer_pooled(<your_valid_data_artifact>, perc_identity = 0.99, min_size = 4)

Docstring

Denoise valid data into zOTUs, then cluster them into OTUs

  This Method Pools All Samples Together, then Extracts Biological Reads Using
  the Unoise3 Algorithm, Finally OTUs are Generated by Clustering zOTUs Using
  the Uclust Algorithm at the user's defined identity threshold. Non-Biological
  Sequence (i.e. Barcodes, Primers) MUST be REMOVED Prior to this step. You
  MUST Also MERGE Your Reads If You are Using PAIRED-END Sequncing Protocol.
  You Can Directly Use the 'Valid-Data' Provided by the Sequencing Center.
  Vsearch was supported in early development but became deprecated for shipment.

Parameters
----------
demultiplexed_seqs : SampleData[SequencesWithQuality]
    The single-end demultiplexed PacBio CCS sequences to be denoised.
trim_left : Int, optional
    Position at which sequences should be trimmed due to low quality. This
    trims the 5' end of the of the input sequences.
trunc_len : Int, optional
    Position at which sequences should be truncated due to decrease in
    quality. This truncates the 3' end of the of the input sequences. Reads that
    are shorter than this value will be discarded. If 0 is provided, no
    truncation or length filtering will be performed.
min_len : Int, optional
    Minimal length for reads to be retained. Reads shorter than this value will be excluded     for subsequent denoising.
max_ee : Float, optional
    Reads with number of expected errors higher than this value will be
    discarded.
perc_identity : Float, optional
    The identity threshold used for OTU clustering. The default is 0.99, which translate to     99% OTUs.
n_threads : Threads, optional
    The number of threads to use for multithreaded processing. If "auto" is
    provided, the value of ( system core count - 3 ) will be used.
min_size : Int, optional
    The minimum abundance of input reads to be retained. For higher sensivity, reducing        minsize to 4 is reasonable. Note: with smaller minsize, there tends to be more errors      in low-abundance zotus.
unoise_alpha : Float, optional
    The default is 2.0. See UNOISE2 paper for definition.
use_vsearch : Bool, optional
    (Deprecated) The deafault is False. If True, vsearch would be introduced as a drop-in      replacement for usearch.

Returns
-------
table : FeatureTable[Frequency]
    The resulting feature table.
representative_sequences : FeatureData[Sequence]
    The resulting feature sequences. Each feature in the feature table will
    be represented by exactly one sequence.
stats : SampleData[USEARCHStats]
    DataFrame containing statistics during each step of the pipeline