qiime dada2 denoise-paired --help
Usage: qiime dada2 denoise-paired [OPTIONS]
This method denoises paired-end sequences, dereplicates them, and filters
chimeras.
该方法对双末端测序数据进行去噪、去重复、以及过滤嵌合体。
Inputs:
--i-demultiplexed-seqs ARTIFACT SampleData[PairedEndSequencesWithQuality]
The paired-end demultiplexed sequences to be
denoised. [required]
Parameters:
--p-trunc-len-f INTEGER
Position at which forward read sequences should be
truncated due to decrease in quality. This truncates
the 3' end of the of the input sequences, which will
be the bases that were sequenced in the last cycles.
Reads that are shorter than this value will be
discarded. After this parameter is applied there must
still be at least a 12 nucleotide overlap between the
forward and reverse reads. If 0 is provided, no
truncation or length filtering will be performed
[required]
由于质量下降，正向read序列应该被截断的位置。这将截断输入序列的3'端，这将是在最后一个循环中被测序的碱基。低于该值的reads将被丢弃。使用该参数后，在正向和反向reads之间必须至少有12个核苷酸重叠。如果设置为0，则不进行截断或长度过滤。
--p-trunc-len-r INTEGER
Position at which reverse read sequences should be
truncated due to decrease in quality. This truncates
the 3' end of the of the input sequences, which will
be the bases that were sequenced in the last cycles.
Reads that are shorter than this value will be
discarded. After this parameter is applied there must
still be at least a 12 nucleotide overlap between the
forward and reverse reads. If 0 is provided, no
truncation or length filtering will be performed
[required]
--p-trim-left-f INTEGER
Position at which forward read sequences should be
trimmed due to low quality. This trims the 5' end of
the input sequences, which will be the bases that
were sequenced in the first cycles. [default: 0]
由于低质量，正向read序列应该被裁剪的位置。这将裁剪输入序列的5'端，这将是在第一个循环中测序的的碱基。
--p-trim-left-r INTEGER
Position at which reverse read sequences should be
trimmed due to low quality. This trims the 5' end of
the input sequences, which will be the bases that
were sequenced in the first cycles. [default: 0]
--p-max-ee-f NUMBER Forward reads with number of expected errors higher
than this value will be discarded. [default: 2.0]
--p-max-ee-r NUMBER Reverse reads with number of expected errors higher
than this value will be discarded. [default: 2.0]
--p-trunc-q INTEGER Reads are truncated at the first instance of a
quality score less than or equal to this value. If
the resulting read is then shorter than `trunc-len-f`
or `trunc-len-r` (depending on the direction of the
read) it is discarded. [default: 2]
--p-pooling-method TEXT Choices('independent', 'pseudo')
The method used to pool samples for denoising.
"independent": Samples are denoised indpendently.
"pseudo": The pseudo-pooling method is used to
approximate pooling of samples. In short, samples are
denoised independently once, ASVs detected in at
least 2 samples are recorded, and samples are
denoised independently a second time, but this time
with prior knowledge of the recorded ASVs and thus
higher sensitivity to those ASVs.
[default: 'independent']
--p-chimera-method TEXT Choices('consensus', 'none', 'pooled')
The method used to remove chimeras. "none": No
chimera removal is performed. "pooled": All reads are
pooled prior to chimera detection. "consensus":
Chimeras are detected in samples individually, and
sequences found chimeric in a sufficient fraction of
samples are removed. [default: 'consensus']
--p-min-fold-parent-over-abundance NUMBER
The minimum abundance of potential parents of a
sequence being tested as chimeric, expressed as a
fold-change versus the abundance of the sequence
being tested. Values should be greater than or equal
to 1 (i.e. parents should be more abundant than the
sequence being tested). This parameter has no effect
if chimera-method is "none". [default: 1.0]
--p-n-threads INTEGER The number of threads to use for multithreaded
processing. If 0 is provided, all available cores
will be used. [default: 1]
--p-n-reads-learn INTEGER
The number of reads to use when training the error
model. Smaller numbers will result in a shorter run
time but a less reliable error model.
[default: 1000000]
--p-hashed-feature-ids / --p-no-hashed-feature-ids
If true, the feature ids in the resulting table will
be presented as hashes of the sequences defining each
feature. The hash will always be the same for the
same sequence so this allows feature tables to be
merged across runs of this method. You should only
merge tables if the exact same parameters are used
for each run. [default: True]
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, and these sequences will be the joined
paired-end sequences. [required]
--o-denoising-stats ARTIFACT SampleData[DADA2Stats]
[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).
--examples Show usage examples and exit.
--citations Show citations and exit.
--help Show this message and exit.
qiime dada2 denoise-single --help
Usage: qiime dada2 denoise-single [OPTIONS]
This method denoises single-end sequences, dereplicates them, and filters
chimeras.
Inputs:
--i-demultiplexed-seqs ARTIFACT SampleData[SequencesWithQuality |
PairedEndSequencesWithQuality]
The single-end demultiplexed sequences to be
denoised. [required]
Parameters:
--p-trunc-len INTEGER Position at which sequences should be truncated due
to decrease in quality. This truncates the 3' end of
the of the input sequences, which will be the bases
that were sequenced in the last cycles. Reads that
are shorter than this value will be discarded. If 0
is provided, no truncation or length filtering will
be performed [required]
--p-trim-left INTEGER Position at which sequences should be trimmed due to
low quality. This trims the 5' end of the of the
input sequences, which will be the bases that were
sequenced in the first cycles. [default: 0]
--p-max-ee NUMBER Reads with number of expected errors higher than
this value will be discarded. [default: 2.0]
--p-trunc-q INTEGER Reads are truncated at the first instance of a
quality score less than or equal to this value. If
the resulting read is then shorter than `trunc-len`,
it is discarded. [default: 2]
--p-pooling-method TEXT Choices('independent', 'pseudo')
The method used to pool samples for denoising.
"independent": Samples are denoised independently.
"pseudo": The pseudo-pooling method is used to
approximate pooling of samples. In short, samples are
denoised independently once, ASVs detected in at
least 2 samples are recorded, and samples are
denoised independently a second time, but this time
with prior knowledge of the recorded ASVs and thus
higher sensitivity to those ASVs.
[default: 'independent']
--p-chimera-method TEXT Choices('consensus', 'none', 'pooled')
The method used to remove chimeras. "none": No
chimera removal is performed. "pooled": All reads are
pooled prior to chimera detection. "consensus":
Chimeras are detected in samples individually, and
sequences found chimeric in a sufficient fraction of
samples are removed. [default: 'consensus']
--p-min-fold-parent-over-abundance NUMBER
The minimum abundance of potential parents of a
sequence being tested as chimeric, expressed as a
fold-change versus the abundance of the sequence
being tested. Values should be greater than or equal
to 1 (i.e. parents should be more abundant than the
sequence being tested). This parameter has no effect
if chimera-method is "none". [default: 1.0]
--p-n-threads INTEGER The number of threads to use for multithreaded
processing. If 0 is provided, all available cores
will be used. [default: 1]
--p-n-reads-learn INTEGER
The number of reads to use when training the error
model. Smaller numbers will result in a shorter run
time but a less reliable error model.
[default: 1000000]
--p-hashed-feature-ids / --p-no-hashed-feature-ids
If true, the feature ids in the resulting table will
be presented as hashes of the sequences defining each
feature. The hash will always be the same for the
same sequence so this allows feature tables to be
merged across runs of this method. You should only
merge tables if the exact same parameters are used
for each run. [default: True]
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-denoising-stats ARTIFACT SampleData[DADA2Stats]
[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).
--examples Show usage examples and exit.
--citations Show citations and exit.
--help Show this message and exit.
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