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ampliconnoise.py – Run AmpliconNoise

Description:

The steps performed by this script are:

  1. Split input sff.txt file into one file per sample
  2. Run scripts required for PyroNoise
  3. Run scripts required for SeqNoise
  4. Run scripts requred for Perseus (chimera removal)
  5. Merge output files into one file similar to the output of split_libraries.py

This script produces a denoised fasta sequence file such as: >PC.355_41 CATGCTGCCTC... ... >PC.636_23 CATGCTGCCTC... ...

Additionally, the intermediate results of the ampliconnoise pipeline are written to an output directory.

Ampliconnoise must be installed and correctly configured, and parallelized steps will be called with mpirun, not qiime’s start_parallel_jobs_torque.py script.

Usage: ampliconnoise.py [options]

Input Arguments:

Note

[REQUIRED]

-m, --mapping_fp
The mapping filepath
-i, --sff_filepath
Sff.txt filepath
-o, --output_filepath
The output file

[OPTIONAL]

-n, --np
Number of processes to use for mpi steps. Default: 2
--chimera_alpha
Alpha value to Class.pl used for chimera removal Default: -3.8228
--chimera_beta
Beta value to Class.pl used for chimera removal Default: 0.62
--seqnoise_resolution
-s parameter passed to seqnoise. Default is 25.0 for titanium, 30.0 for flx
-d, --output_dir
Directory for ampliconnoise intermediate results. Default is output_filepath_dir
-p, --parameter_fp
Path to the parameter file, which specifies changes to the default behavior. See http://www.qiime.org/documentation/file_formats.html#qiime-parameters. [if omitted, default values will be used]
-f, --force
Force overwrite of existing output directory (note: existing files in output_dir will not be removed) [default: False]
-w, --print_only
Print the commands but don’t call them – useful for debugging [default: False]
--suppress_perseus
Omit perseus from ampliconnoise workflow
--platform
Sequencing technology, options are ‘titanium’,’flx’. [default: flx]

Output:

a fasta file of sequences, with labels as:’>sample1_0’ , ‘>sample1_1’ ...

Run ampliconnoise, write output to anoise_out.fna, compatible with output of split_libraries.py

ampliconnoise.py -i Fasting_Example.sff.txt -m Fasting_Map.txt -o anoise_out.fna

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