Docstring:
Usage: qiime deblur denoise-other [OPTIONS]
Perform sequence quality control for Illumina data using the Deblur
workflow, including positive alignment-based filtering. Only forward reads
are supported at this time. This mode of execution is particularly useful
when operating on non-16S data. For example, to apply Deblur to 18S data,
you would want to specify a reference composed of 18S sequences in order to
filter out sequences which do not appear to be 18S. The assessment is
performed by local alignment using SortMeRNA with a permissive e-value
threshold.
Inputs:
--i-demultiplexed-seqs ARTIFACT SampleData[SequencesWithQuality |
PairedEndSequencesWithQuality | JoinedSequencesWithQuality]
The demultiplexed sequences to be denoised.
[required]
--i-reference-seqs ARTIFACT FeatureData[Sequence]
Positive filtering database. Keep all sequences
aligning to these sequences. [required]
Parameters:
--p-trim-length INTEGER
Sequence trim length, specify -1 to disable
trimming. [required]
--p-left-trim-len INTEGER
Range(0, None) Sequence trimming from the 5' end. A value of 0 will
disable this trim. [default: 0]
--p-sample-stats / --p-no-sample-stats
If true, gather stats per sample. [default: False]
--p-mean-error NUMBER The mean per nucleotide error, used for original
sequence estimate. [default: 0.005]
--p-indel-prob NUMBER Insertion/deletion (indel) probability (same for N
indels). [default: 0.01]
--p-indel-max INTEGER Maximum number of insertion/deletions. [default: 3]
--p-min-reads INTEGER Retain only features appearing at least min-reads
times across all samples in the resulting feature
table. [default: 10]
--p-min-size INTEGER In each sample, discard all features with an
abundance less than min-size. [default: 2]
--p-jobs-to-start NTHREADS
Number of jobs to start (if to run in parallel).
[default: 1]
--p-hashed-feature-ids / --p-no-hashed-feature-ids
If true, hash the feature IDs. [default: True]
Outputs:
--o-table ARTIFACT FeatureTable[Frequency]
The resulting denoised feature table. [required]
--o-representative-sequences ARTIFACT FeatureData[Sequence]
The resulting feature sequences. [required]
--o-stats ARTIFACT Per-sample stats if requested.
DeblurStats [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.deblur.methods import denoise_other
Docstring:
Deblur sequences using a user-specified positive filter.
Perform sequence quality control for Illumina data using the Deblur
workflow, including positive alignment-based filtering. Only forward reads
are supported at this time. This mode of execution is particularly useful
when operating on non-16S data. For example, to apply Deblur to 18S data,
you would want to specify a reference composed of 18S sequences in order to
filter out sequences which do not appear to be 18S. The assessment is
performed by local alignment using SortMeRNA with a permissive e-value
threshold.
Parameters
----------
demultiplexed_seqs : SampleData[SequencesWithQuality | PairedEndSequencesWithQuality | JoinedSequencesWithQuality]
The demultiplexed sequences to be denoised.
reference_seqs : FeatureData[Sequence]
Positive filtering database. Keep all sequences aligning to these
sequences.
trim_length : Int
Sequence trim length, specify -1 to disable trimming.
left_trim_len : Int % Range(0, None), optional
Sequence trimming from the 5' end. A value of 0 will disable this trim.
sample_stats : Bool, optional
If true, gather stats per sample.
mean_error : Float, optional
The mean per nucleotide error, used for original sequence estimate.
indel_prob : Float, optional
Insertion/deletion (indel) probability (same for N indels).
indel_max : Int, optional
Maximum number of insertion/deletions.
min_reads : Int, optional
Retain only features appearing at least min_reads times across all
samples in the resulting feature table.
min_size : Int, optional
In each sample, discard all features with an abundance less than
min_size.
jobs_to_start : Threads, optional
Number of jobs to start (if to run in parallel).
hashed_feature_ids : Bool, optional
If true, hash the feature IDs.
Returns
-------
table : FeatureTable[Frequency]
The resulting denoised feature table.
representative_sequences : FeatureData[Sequence]
The resulting feature sequences.
stats : DeblurStats
Per-sample stats if requested.
