Docstring:
Usage: qiime feature-table filter-features-conditionally [OPTIONS]
Filter features based on the relative abundance in a certain portion of
samples (i.e., features must have a relative abundance of at least
`abundance` in at least `prevalence` number of samples). Any samples with a
frequency of zero after feature filtering will also be removed.
Inputs:
--i-table ARTIFACT FeatureTable[Frequency¹ | RelativeFrequency² |
PresenceAbsence³ | Composition⁴]
The feature table from which features should be
filtered. [required]
Parameters:
--p-abundance PROPORTION
Range(0, 1) The minimum relative abundance for a feature to be
retained. [required]
--p-prevalence PROPORTION
Range(0, 1) The minimum portion of samples that a feature must
have a relative abundance of at least `abundance` to be
retained. [required]
--p-allow-empty-table / --p-no-allow-empty-table
If true, the filtered table may be empty. Default
behavior is to raise an error if the filtered table is
empty. [default: False]
Outputs:
--o-filtered-table ARTIFACT FeatureTable[Frequency¹ | RelativeFrequency²
| PresenceAbsence³ | Composition⁴]
The resulting feature table filtered by feature.
[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.
Examples:
# ### example: feature table filter features conditionally
# Retain only features with at least 1%% abundance in at least 34%% of
# samples.
qiime feature-table filter-features-conditionally \
--i-table feature-table.qza \
--p-abundance 0.01 \
--p-prevalence 0.34 \
--o-filtered-table filtered-table.qza
Import:
from qiime2.plugins.feature_table.methods import filter_features_conditionally
Docstring:
Filter features from a table based on abundance and prevalence
Filter features based on the relative abundance in a certain portion of
samples (i.e., features must have a relative abundance of at least
`abundance` in at least `prevalence` number of samples). Any samples with a
frequency of zero after feature filtering will also be removed.
Parameters
----------
table : FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]
The feature table from which features should be filtered.
abundance : Float % Range(0, 1)
The minimum relative abundance for a feature to be retained.
prevalence : Float % Range(0, 1)
The minimum portion of samples that a feature must have a relative
abundance of at least `abundance` to be retained.
allow_empty_table : Bool, optional
If true, the filtered table may be empty. Default behavior is to raise
an error if the filtered table is empty.
Returns
-------
filtered_table : FeatureTable[Frequency¹ | RelativeFrequency² | PresenceAbsence³ | Composition⁴]
The resulting feature table filtered by feature.
