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swarm(1) USER COMMANDS swarm(1)

NAME

swarm — find clusters of nearly-identical nucleotide amplicons

SYNOPSIS

swarm -h|v

High-precision clustering:

swarm [filename]
swarm [-d 1] [-nrz] [-a int] [-i filename] [-l filename] [-o filename] [-s filename] [-t int] [-u filename] [-w filename] [filename]
swarm [-d 1] -f [-nrz] [-a int] [-b int] [-c|y int] [-i filename] [-l filename] [-o filename] [-s filename] [-t int] [-u filename] [-w filename] [filename]

Conservative clustering:

swarm -d 2+ [-nrz] [-a int] [-e int] [-g int] [-i filename] [-l filename] [-m int] [-o filename] [-p int] [-s filename] [-t int] [-u filename] [-w filename] [filename]

Dereplication (merge strictly identical sequences):

swarm -d 0 [-rz] [-a int] [-i filename] [-l filename] [-o filename] [-s filename] [-u filename] [-w filename] [filename]

DESCRIPTION

Environmental or clinical molecular studies generate large volumes of amplicons (e.g., 16S or 18S SSU-rRNA sequences) that need to be clustered into molecular operational taxonomic units (OTUs). Common clustering methods are based on greedy, input-order dependent algorithms, with arbitrary selection of global cluster size and cluster centroids. To address that problem, we developed swarm, a fast and robust method that recursively groups amplicons with d or less differences (i.e. substitutions, insertions or deletions). swarm produces natural and stable clusters centered on local peaks of abundance, mostly free from input-order dependency induced by centroid selection.

Exact clustering is impractical on large data sets when using a naïve all-vs-all approach (more precisely a 2-combination without repetitions), as it implies unrealistic numbers of pairwise comparisons. swarm is based on a maximum number of differences d between two amplicons, and focuses only on very close local relationships. For d = 1, the default value, swarm uses an algorithm of linear complexity that generates all possible single mutations and performs exact-string matching by comparing hash-values. For d = 2 or greater, swarm uses an algorithm of quadratic complexity that performs pairwise string comparisons. An efficient k-mer-based filtering and an astute use of comparisons results obtained during the clustering process allows swarm to avoid most of the amplicon comparisons needed in a naïve approach. To speed up the remaining amplicon comparisons, swarm implements an extremely fast Needleman-Wunsch algorithm making use of the Streaming SIMD Extensions (SSE2) of modern x86-64 CPUs, or NEON instructions of ARM-64 CPUs. If SSE2 instructions are not available, swarm exits with an error message.

swarm can read nucleotide amplicons in fasta format from a normal file or from the standard input (using a pipe or a redirection). The amplicon header is defined as the string comprised between the '>' symbol and the first space or the end of the line, whichever comes first. Each header must end with an abundance annotation representing the amplicon copy number and defined as '_' followed by a positive integer. See option -z for input data using usearch/vsearch's abundance annotation format (';size=integer[;]'). Once stripped from the abundance annotation, the remaining part of the header is call the label. In summary:


>header[[:blank:]] and header = label_[1-9][0-9]*$

Abundance annotations play a crucial role in the clustering process, and swarm exits with an error message if that information is not available. As swarm outputs lists of amplicon labels, amplicon labels must be unique to avoid any ambiguity; swarm exits with an error message if labels are not unique. The amplicon sequence is defined as a string of [ACGT] or [ACGU] symbols (case insensitive, 'U' is replaced with 'T' internally), starting after the end of the header line and ending before the next header line or the file end; swarm silently removes newline symbols ('\n' or '\r') and exits with an error message if any other symbol is present. Lastly, if sequences are not all unique, i.e. were not properly dereplicated, swarm will exit with an error message.

Clusters are written to output files (specified with -i, -o, -s and -u) by decreasing abundance of their seed sequences, and then by alphabetical order of seed sequence labels. An exception to that is the -w (--seeds) output, which is sorted by decreasing cluster abundance (sum of abundances of all sequences in the cluster), and then by alphabetical order of seed sequence labels. This is particularly useful for post-clustering steps, such as de novo chimera detection, that require clusters to be sorted by decreasing abundances.

General options

display this help and exit successfully.
number of computation threads to use. Values between 1 and 256 are accepted, but we recommend to use a number of threads lesser or equal to the number of available CPU cores. Default number of threads is 1.
output version information and exit successfully.
--
delimit the option list. Later arguments, if any, are treated as operands even if they begin with '-'. For example, 'swarm -- -file.fasta' reads from the file '-file.fasta'.

Clustering options

maximum number of differences allowed between two amplicons, meaning that two amplicons will be grouped if they have integer (or less) differences. This is swarm's most important parameter. The number of differences is calculated as the number of mismatches (substitutions, insertions or deletions) between the two amplicons once the optimal pairwise global alignment has been found (see 'pairwise alignment advanced options' to influence that step). Any integer from 0 to 255 can be used, but high d values will decrease the taxonomical resolution of swarm results. Commonly used d values are 1, 2 or 3, rarely higher. When using d = 0, swarm will output results corresponding to a strict dereplication of the dataset, i.e. merging identical amplicons. Warning, whatever the d value, swarm requires fasta entries to present abundance values. Default number of differences d is 1.
when working with d = 1, deactivate the built-in OTU refinement (not recommended). Amplicon abundance values are used to identify transitions among in-contact OTUs and to separate them, yielding higher-resolution clustering results. That option prevents that separation, and in practice, allows the creation of a link between amplicons A and B, even if the abundance of B is higher than the abundance of A.

Fastidious options

when using the option --fastidious (-f), define the minimum mass of a large OTU. By default, an OTU with a mass of 3 or more is considered large. Conversely, an OTU is small if it has a mass of less than 3, meaning that it is composed of either one amplicon of abundance 2, or two amplicons of abundance 1. Any positive value greater than 1 can be specified. Using higher boundary values will speed up the second pass, but also reduce the taxonomical resolution of swarm results. Default mass of a large OTU is 3.
when using the option --fastidious (-f), define swarm's maximum memory footprint (in megabytes). swarm will adjust the --bloom-bits (-y) value of the Bloom filter to fit within the specified amount of memory. The value must be at least 8.
when working with d = 1, perform a second clustering pass to reduce the number of small OTUs (recommended option). During the first clustering pass, an intermediate amplicon can be missing for purely stochastic reasons, interrupting the aggregation process. The fastidious option will create virtual amplicons, allowing to graft small OTUs upon bigger ones. By default, an OTU is small if it has a mass of 2 or less (see the --boundary option to modify that value). To speed things up, swarm uses a Bloom filter to store intermediate results. Warning, the second clustering pass can be 2 to 3 times slower than the first pass and requires much more memory to store the virtual amplicons in Bloom filters. See the options --bloom-bits (-y) or --ceiling (-c) to control the memory footprint of the Bloom filter. The fastidious option modifies clustering results: the output files produced by the options --log (-l), --output-file (-o), --mothur (-r), --uclust-file, and --seeds (-w) are updated to reflect these modifications; the file --statistics-file (-s) is partially updated (columns 6 and 7 are not updated); the output file --internal-structure (-i) is partially updated (column 5 is not updated for amplicons that belonged to the small OTU).
when using the option --fastidious (-f), define the size (in bits) of each entry in the Bloom filter. That option allows to balance the efficiency (i.e. speed) and the memory footprint of the Bloom filter. Large values will make the Bloom filter more efficient but will require more memory. Any value between 2 and 64 can be used. Default value is 16. See the --ceiling (-c) option for an alternative way to control the memory footprint.

Input/output options

set abundance value to use when some or all amplicons in the input file lack abundance values (_integer, or ;size=integer; when using -z). Warning, it is not recommended to use swarm on datasets where abundance values are all identical. We provide that option as a courtesy to advanced users, please use it carefully. swarm exits with an error message if abundance values are missing and if this option is not used.
output all pairs of nearly-identical amplicons to filename using a five-columns tab-delimited format:
1.
amplicon A label (header without abundance annotations).
2.
amplicon B label (header without abundance annotations).
3.
number of differences between amplicons A and B (positive integer).
4.
OTU number (positive integer). OTUs are numbered in their order of delineation, starting from 1. All pairs of amplicons belonging to the same OTU will receive the same number.
5.
cummulated number of steps from the OTU seed to amplicon B (positive integer). When using the option --fastidious (-f), the actual number of steps between grafted amplicons and the OTU seed cannot be re-computed efficiently and is always set to 2 for the amplicon pair linking the small OTU to the big OTU. Cummulated number of steps in the small OTU (if any) are left unchanged.
output all messages to filename instead of standard error, with the exception of error messages of course. That option is useful in situations where writing to standard error is problematic (for example, with certain job schedulers).
output clustering results to filename. Results consist of a list of OTUs, one OTU per line. An OTU is a list of amplicon headers separated by spaces. That output format can be modified by the option --mothur (-r). Default is to write to standard output.
output clustering results in a format compatible with Mothur. That option modifies swarm's default output format.
output statistics to filename. The file is a tab-separated table with one OTU per row and seven columns of information:
1.
number of unique amplicons in the OTU,
2.
total abundance of amplicons in the OTU,
3.
label of the initial seed (header without abundance annotations),
4.
abundance of the initial seed,
5.
number of amplicons with an abundance of 1 in the OTU,
6.
maximum number of iterations before the OTU reached its natural limit,
7.
cummulated number of steps along the path joining the seed and the furthermost amplicon in the OTU. Please note that the actual number of differences between the seed and the furthermost amplicon is usually much smaller. When using the option --fastidious (-f), grafted amplicons are not taken into account.
output clustering results in filename using a tab-separated uclust-like format with 10 columns and 3 different type of entries (S, H or C). That option does not modify swarm's default output format. Each fasta sequence in the input file can be either a cluster centroid (S) or a hit (H) assigned to a cluster. Cluster records (C) summarize information (size, centroid header) for each cluster. Column content varies with the type of entry (S, H or C):
1.
Record type: S, H, or C.
2.
Cluster number (zero-based).
3.
Centroid length (S), query length (H), or cluster size (C).
4.
Percentage of similarity with the centroid sequence (H), or set to '*' (S, C).
5.
Match orientation + or - (H), or set to '*' (S, C).
6.
Not used, always set to '*' (S, C) or to zero (H).
7.
Not used, always set to '*' (S, C) or to zero (H).
8.
set to '*' (S, C) or, for H, compact representation of the pairwise alignment using the CIGAR format (Compact Idiosyncratic Gapped Alignment Report): M (match), D (deletion) and I (insertion). The equal sign '=' indicates that the query is identical to the centroid sequence.
9.
Header of the query sequence (H), or of the centroid sequence (S, C).
10.
Header of the centroid sequence (H), or set to '*' (S, C).
output OTU representative sequences to filename in fasta format. The abundance value of each OTU representative is the sum of the abundances of all the amplicons in the OTU. Fasta headers are formated as follows: '>label_integer', or '>label;size=integer;' if the -z option is used, and sequences are uppercased. Sequences are sorted by decreasing abundance, and then by alphabetical order of sequence labels.
accept amplicon abundance values in usearch/vsearch's style (>label;size=integer[;]). That option influences the abundance annotation style used in swarm's standard output (-o), as well as the output of options -r, -u and -w.

Pairwise alignment advanced options

when using d > 1, swarm recognizes advanced command-line options modifying the pairwise global alignment scoring parameters:

Default reward for a nucleotide match is 5.
Default penalty for a nucleotide mismatch is 4.
Default gap opening penalty is 12.
Default gap extension penalty is 4.

As swarm focuses on close relationships (e.g., d = 2 or 3), clustering results are resilient to pairwise alignment model parameters modifications. When clustering using a higher d value, modifying model parameters has a stronger impact.

EXAMPLES

Clusterize the compressed data set myfile.fasta into OTUs using the finest resolution possible (1 difference by default, built-in breaking, fastidious option) using 4 computation threads. OTUs are written to the file myfile.swarms, and OTU representatives are written to myfile.representatives.fasta:

zcat myfile.fasta.gz | \


    swarm \


        -t 4 \


        -f \


        -w myfile.representatives.fasta \


        -o /dev/null






AUTHORS


Concept by Frédéric Mahé, implementation by
    Torbjørn Rognes.






CITATION


Mahé F, Rognes T, Quince C, de Vargas C, Dunthorn M. (2014)
    Swarm: robust and fast clustering method for amplicon-based studies.
    PeerJ 2:e593
    https://doi.org/10.7717/peerj.593.


Mahé F, Rognes T, Quince C, de Vargas C, Dunthorn M. (2015)
    Swarm v2: highly-scalable and high-resolution amplicon clustering.
    PeerJ 3:e1420
    https://doi.org/10.7717/peerj.1420.






REPORTING BUGS


Submit suggestions and bug-reports at
    https://github.com/torognes/swarm/issues,
    send a pull request at
    https://github.com/torognes/swarm,
    or compose a friendly or curmudgeonly e-mail to
    Frédéric
    Mahé and
    Torbjørn
  Rognes.






AVAILABILITY


Source code and binaries available at
    https://github.com/torognes/swarm.






COPYRIGHT


Copyright (C) 2012-2019 Frédéric Mahé &
    Torbjørn Rognes


This program is free software: you can redistribute it and/or
    modify it under the terms of the GNU Affero General Public License as
    published by the Free Software Foundation, either version 3 of the License,
    or any later version.


This program is distributed in the hope that it will be useful,
    but WITHOUT ANY WARRANTY; without even the implied warranty of
    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Affero
    General Public License for more details.


You should have received a copy of the GNU Affero General Public
    License along with this program. If not, see
    http://www.gnu.org/licenses/.






SEE ALSO


swipe, an extremely fast Smith-Waterman database search
    tool by Torbjørn Rognes (available at
    https://github.com/torognes/swipe).


vsearch, an open-source re-implementation of the classic
    uclust clustering method (by Robert C. Edgar), along with other amplicon
    filtering and searching tools. vsearch is implemented by
    Torbjørn Rognes and documented by Frédéric Mahé,
    and is available at
    https://github.com/torognes/vsearch.






VERSION HISTORY


New features and important modifications of swarm (short
    lived or minor bug releases are not mentioned):





  

  
Version 3.0.0 introduces a faster algorithm for d = 1, and a
      reduced memory footprint. Swarm has been ported to Windows x86-64,
      GNU/Linux ARM 64, and GNU/Linux POWER8. Internal code has been modernized,
      hardened, and thoroughly tested. Strict dereplication of input sequences
      is now mandatory. The --seeds option (-w) now outputs results sorted by
      decreasing abundance, and then by alphabetical order of sequence
    labels.

  

  
Version 2.2.2 fixes a bug that would cause swarm to wait forever in very
      rare cases when multiple threads were used.

  

  
Version 2.2.1 fixes a memory allocation bug for d = 1 and
      duplicated sequences.

  

  
Version 2.2.0 fixes several problems and improves usability. Corrected
      output to structure and uclust files when using fastidious mode. Corrected
      abundance output in some cases. Added check for duplicated sequences and
      fixed check for duplicated sequence IDs. Checks for empty sequences. Sorts
      sequences by additional fields to improve stability. Improves
      compatibility with compilers and operating systems. Outputs sequences in
      upper case. Allows 64-bit abundances. Shows message when waiting for input
      from stdin. Improves error messages and warnings. Improves checking of
      command line options. Fixes remaining errors reported by test suite.
      Updates documentation.

  

  
Version 2.1.13 removes a bug with the progress bar when writing
    seeds.

  

  
Version 2.1.12 removes a debugging message.

  

  
Version 2.1.11 fixes two bugs related to the SIMD implementation of
      alignment that might result in incorrect alignments and scores. The bug
      only applies when d > 1.

  

  
Version 2.1.10 fixes two bugs related to gap penalties of alignments. The
      first bug may lead to wrong aligments and similarity percentages reported
      in UCLUST (.uc) files. The second bug makes swarm use a slightly higher
      gap extension penalty than specified. The default gap extension penalty
      used have actually been 4.5 instead of 4.

  

  
Version 2.1.9 fixes errors when compiling with GCC version 6.

  

  
Version 2.1.8 fixes a rare bug triggered when clustering extremely short
      undereplicated sequences. Also, alignment parameters are not shown when
      d = 1.

  

  
Version 2.1.7 fixes a bug in the output of seeds with the -w option when
      d > 1 that was not properly fixed in version 2.1.6. It also
      handles ascii character #13 (CR) in FASTA files better. Swarm will now
      exit with status 0 if the -h or the -v option is specified. The help text
      and some error messages have been improved.

  

  
Version 2.1.6 fixes problems with older compilers that do not have the
      x86intrin.h header file. It also fixes a bug in the output of seeds with
      the -w option when d > 1.

  

  
Version 2.1.5 fixes minor bugs.

  

  
Version 2.1.4 fixes minor bugs in the swarm algorithm used for d =
      1.

  

  
Version 2.1.3 adds checks of numeric option arguments.

  

  
Version 2.1.1 fixes a bug with the fastidious option that caused it to
      ignore some connections between large and small OTUs.

  

  
Version 2.1.0 marks the first official release of swarm v2.

  

  
Version 2.0.7 writes abundance information in usearch style when using
      options -w (--seeds) in combination with -z (--usearch-abundance).

  

  
Version 2.0.6 fixes a minor bug.

  

  
Version 2.0.5 improves the implementation of the fastidious option and
      adds options to control memory usage of the Bloom filter (-y and -c). In
      addition, an option (-w) allows to output OTU representatives sequences
      with updated abundances (sum of all abundances inside each OTU). This
      version also enables swarm to run with d = 0.

  

  
Version 2.0.4 includes a fully parallelised implementation of the
      fastidious option.

  

  
Version 2.0.3 includes a working implementation of the fastidious option,
      but only the initial clustering is parallelized.

  

  
Version 2.0.2 fixes SSSE3 problems.

  

  
Version 2.0.1 is a development version that contains a partial
      implementation of the fastidious option, but it is not usable yet.

  

  
Version 2.0.0 is faster and easier to use, providing new output options
      (--internal-structure and --log), new control options (--boundary,
      --fastidious, --no-otu-breaking), and built-in OTU refinement (no need to
      use the python script anymore). When using default parameters, a novel and
      considerably faster algorithmic approach is used, guaranteeing
      swarm's scalability.

  

  
Version 1.2.21 is supposed to fix some problems related to the use of the
      SSSE3 CPU instructions which are not always available.

  

  
Version 1.2.20 presents a production-ready version of the alternative
      algorithm (option -a), with optional built-in OTU breaking (option -n).
      That alternative algorithmic approach (usable only with d = 1) is
      considerably faster than currently used clustering algorithms, and can
      deal with datasets of 100 million unique amplicons or more in a few hours.
      Of course, results are rigourously identical to the results previously
      produced with swarm. That release also introduces new options to control
      swarm output (options -i and -l).

  

  
Version 1.2.19 fixes a problem related to abundance information when the
      sequence label includes multiple underscore characters.

  

  
Version 1.2.18 reenables the possibility of reading sequences from
      stdin if no file name is specified on the command line. It also
      fixes a bug related to CPU features detection.

  

  
Version 1.2.17 fixes a memory allocation bug introduced in version
    1.2.15.

  

  
Version 1.2.16 fixes a bug in the abundance sort introduced in version
      1.2.15.

  

  
Version 1.2.15 sorts the input sequences in order of decreasing abundance
      unless they are detected to be sorted already. When using the alternative
      algorithm for d = 1 it also sorts all subseeds in order of
      decreasing abundance.

  

  
Version 1.2.14 fixes a bug in the output with the --swarm_breaker option
      (-b) when using the alternative algorithm (-a).

  

  
Version 1.2.12 introduces an option --alternative-algorithm to use an
      extremely fast, experimental clustering algorithm for the special case
      d = 1. Multithreading scalability of the default algorithm has been
      noticeably improved.

  

  
Version 1.2.10 allows amplicon abundances to be specified using the
      usearch style in the sequence header (e.g. '>id;size=1') when the -z
      option is chosen.

  

  
Version 1.2.8 fixes an error with the gap extension penalty. Previous
      versions used a gap penalty twice as large as intended. That bug
      correction induces small changes in clustering results.

  

  
Version 1.2.6 introduces an option --mothur to output clustering results
      in a format compatible with the microbial ecology community analysis
      software suite Mothur (
      https://www.mothur.org/).

  

  
Version 1.2.5 removes the need for a POPCNT hardware instruction to be
      present. swarm now automatically checks whether POPCNT is available
      and uses a slightly slower software implementation if not. Only basic SSE2
      instructions are now required to run swarm.

  

  
Version 1.2.4 introduces an option --break-swarms to output all pairs of
      amplicons with d differences to standard error. That
      option is used by the companion script `swarm_breaker.py` to refine
      swarm results. The syntax of the inline assembly code is changed
      for compatibility with more compilers.

  

  
Version 1.2 greatly improves speed by using alignment-free comparisons of
      amplicons based on k-mer word content. For each amplicon, the
      presence-absence of all possible 5-mers is computed and recorded in a
      1024-bits vector. Vector comparisons are extremely fast and drastically
      reduce the number of costly pairwise alignments performed by swarm.
      While remaining exact, swarm 1.2 can be more than 100-times faster
      than swarm 1.1, when using a single thread with a large set of
      sequences. The minor version 1.1.1, published just before, adds
      compatibility with Apple computers, and corrects an issue in the pairwise
      global alignment step that could lead to sub-optimal alignments.

  

  
Version 1.1 introduces two new important options: the possibility to
      output clustering results using the uclust output format, and the
      possibility to output detailed statistics on each OTU. swarm 1.1 is
      also faster: new filterings based on pairwise amplicon sequence lengths
      and composition comparisons reduce the number of pairwise alignments
      needed and speed up the clustering.

  

  
First public release.











  

    October 24, 2019
    version 3.0.0