Docstring:
Usage: qiime vsearch uchime-denovo [OPTIONS]
Apply the vsearch uchime_denovo method to identify chimeric feature
sequences. The results of this method can be used to filter chimeric
features from the corresponding feature table. For more details, please
refer to the vsearch documentation.
Inputs:
--i-sequences ARTIFACT FeatureData[Sequence]
The feature sequences to be chimera-checked.
[required]
--i-table ARTIFACT FeatureTable[Frequency]
Feature table (used for computing total feature
abundances). [required]
Parameters:
--p-dn NUMBER No vote pseudo-count, corresponding to the
Range(0.0, None) parameter n in the chimera scoring function.
[default: 1.4]
--p-mindiffs INTEGER Minimum number of differences per segment.
Range(1, None) [default: 3]
--p-mindiv NUMBER Minimum divergence from closest parent.
Range(0.0, None) [default: 0.8]
--p-minh PROPORTION Range(0.0, 1.0, inclusive_end=True)
Minimum score (h). Increasing this value tends to
reduce the number of false positives and to decrease
sensitivity. [default: 0.28]
--p-xn NUMBER Range(1.0, None, inclusive_start=False)
No vote weight, corresponding to the parameter beta
in the scoring function. [default: 8.0]
Outputs:
--o-chimeras ARTIFACT FeatureData[Sequence]
The chimeric sequences. [required]
--o-nonchimeras ARTIFACT FeatureData[Sequence]
The non-chimeric sequences. [required]
--o-stats ARTIFACT Summary statistics from chimera checking.
UchimeStats [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.
Import:
from qiime2.plugins.vsearch.methods import uchime_denovo
Docstring:
De novo chimera filtering with vsearch.
Apply the vsearch uchime_denovo method to identify chimeric feature
sequences. The results of this method can be used to filter chimeric
features from the corresponding feature table. For more details, please
refer to the vsearch documentation.
Parameters
----------
sequences : FeatureData[Sequence]
The feature sequences to be chimera-checked.
table : FeatureTable[Frequency]
Feature table (used for computing total feature abundances).
dn : Float % Range(0.0, None), optional
No vote pseudo-count, corresponding to the parameter n in the chimera
scoring function.
mindiffs : Int % Range(1, None), optional
Minimum number of differences per segment.
mindiv : Float % Range(0.0, None), optional
Minimum divergence from closest parent.
minh : Float % Range(0.0, 1.0, inclusive_end=True), optional
Minimum score (h). Increasing this value tends to reduce the number of
false positives and to decrease sensitivity.
xn : Float % Range(1.0, None, inclusive_start=False), optional
No vote weight, corresponding to the parameter beta in the scoring
function.
Returns
-------
chimeras : FeatureData[Sequence]
The chimeric sequences.
nonchimeras : FeatureData[Sequence]
The non-chimeric sequences.
stats : UchimeStats
Summary statistics from chimera checking.
