unoise2 command
See also
UNOISE paper
Should I use UPARSE or UNOISE?
Uses the UNOISE algorithm to perform denoising (error-correction) of amplicon reads.
Input is a set of quality-filtered unique read sequences with size=nnn; abundance annotations. See UNOISE pipeline for details of how reads should be pre-processed. The input should be a complete set of reads without any clustering (except for finding uniques), so for example you should not use 97% OTUs as input. It is ok to run unoise on the FASTQs for a single sample, though I generally recommend pooling samples before denoising.
See Tutorials for example scripts & data.
Errors are corrected as follows:
- Reads with sequencing error are identified and
corrected.
- Chimeras are removed.
-
PhiX sequences are removed.
The algorithm is designed for Illumina reads,
it does not work as well on 454, Ion
Torrent or PacBio reads.
Corrected biological sequences are written to the -fastaout file. Labels are formatted as Otunnn;Uniqlabel; where nnn is 1, 2, 3... and Uniqlabel is the label from the input file (truncated at the first semi-colon, to strip any annotations).
Corrected amplicon sequences are written to the -ampout fle in FASTA format. These include chimeras, so this output file is not usually used in a production pipeline but may be useful for investigating chimera formation rates and the accuracy of chimera detection. Labels are formatted as Ampnnn;uniq=Uniqlabel;uniqsize=u;size=s; where nnn is 1, 2, 3..., Uniqulabel is the label in the input file, truncated at the first semi-colon, u is the size= annotation from the input file and s is the total size of reads derived from this amplicon.
An OTU table can be generated using usearch_global. (This page previously suggested using -otudbout and -search_exact, but that method is less sensitive).
The -minampsize option specifies the minimum abundance (size= annotation) for an error-corrected amplicon. Default is 4.
The -unoise_alpha option specifies the alpha parameter (see UNOISE2 paper for definition). Default is 2.0.
Example
usearch -unoise2 uniques.fa -fastaout
denoised.fa -otudbout db.fa