Fork me on GitHub

summarize: Summarize counts per sample.ΒΆ

Docstring:

Usage: qiime demux summarize [OPTIONS]

  Summarize counts per sample for all samples, and generate interactive
  positional quality plots based on `n` randomly selected sequences.

Inputs:
  --i-data ARTIFACT SampleData[SequencesWithQuality |
    PairedEndSequencesWithQuality | JoinedSequencesWithQuality]
                       The demultiplexed sequences to be summarized.
                                                                    [required]
Parameters:
  --p-n INTEGER        The number of sequences that should be selected at
                       random for quality score plots. The quality plots will
                       present the average positional qualities across all of
                       the sequences selected. If input sequences are paired
                       end, plots will be generated for both forward and
                       reverse reads for the same `n` sequences.
                                                              [default: 10000]
Outputs:
  --o-visualization VISUALIZATION
                                                                    [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).
  --citations          Show citations and exit.
  --help               Show this message and exit.

Import:

from qiime2.plugins.demux.visualizers import summarize

Docstring:

Summarize counts per sample.

Summarize counts per sample for all samples, and generate interactive
positional quality plots based on `n` randomly selected sequences.

Parameters
----------
data : SampleData[SequencesWithQuality | PairedEndSequencesWithQuality | JoinedSequencesWithQuality]
    The demultiplexed sequences to be summarized.
n : Int, optional
    The number of sequences that should be selected at random for quality
    score plots. The quality plots will present the average positional
    qualities across all of the sequences selected. If input sequences are
    paired end, plots will be generated for both forward and reverse reads
    for the same `n` sequences.

Returns
-------
visualization : Visualization