Re-cluster sequences of an object of class physeq or cluster a list of DNA sequences using SWARM

A wrapper of SWARM software.

Usage

swarm_clustering(
  physeq = NULL,
  dna_seq = NULL,
  d = 1,
  swarmpath = "swarm",
  vsearch_path = "vsearch",
  nproc = 1,
  swarm_args = "--fastidious",
  tax_adjust = 0,
  keep_temporary_files = FALSE
)

Arguments

physeq

(required): a phyloseq-class object obtained using the phyloseq package.

dna_seq

NOT WORKING FOR THE MOMENT You may directly use a character vector of DNA sequences in place of physeq args. When physeq is set, dna sequences take the value of physeq@refseq

d

(default: 1) maximum number of differences allowed between two amplicons, meaning that two amplicons will be grouped if they have d (or less) differences

swarmpath

(default: swarm) path to swarm

vsearch_path

(default: vsearch) path to vsearch, used only if physeq is NULL and dna_seq is provided.

nproc

(default: 1) Set to number of cpus/processors to use for the clustering

swarm_args

(default : "–fastidious") a one length character element defining other parameters to passed on to swarm See other possible methods in the SWARM pdf manual

tax_adjust

(Default 0) See the man page of merge_taxa_vec() for more details. To conserved the taxonomic rank of the most abundant ASV,

keep_temporary_files

(logical, default: FALSE) Do we keep temporary files ?

temp.fasta (refseq in fasta or dna_seq sequences)
temp_output (classical output of SWARM)
temp_uclust (clusters output of SWARM)

Value

A new object of class physeq or a list of cluster if dna_seq args was used.

Details

This function use the merge_taxa_vec function to merge taxa into clusters. By default tax_adjust = 0. See the man page of merge_taxa_vec().

This function is mainly a wrapper of the work of others. Please cite SWARM.

References

SWARM can be downloaded from https://github.com/torognes/swarm/.

SWARM can be downloaded from https://github.com/torognes/swarm. More information in the associated publications doi:10.1093/bioinformatics/btab493 and doi:10.7717/peerj.593

Examples

summary_plot_pq(data_fungi)
#> Cleaning suppress 0 taxa and 0 samples.

system2("swarm", "-h")

data_fungi_swarm <- swarm_clustering(data_fungi)
summary_plot_pq(data_fungi_swarm)
#> Cleaning suppress 0 taxa and 0 samples.


sequences_ex <- c(
  "TACCTATGTTGCCTTGGCGGCTAAACCTACCCGGGATTTGATGGGGCGAATTAATAACGAATTCATTGAATCA",
  "TACCTATGTTGCCTTGGCGGCTAAACCTACCCGGGATTTGATGGGGCGAATTACCTGGTAAGGCCCACTT",
  "TACCTATGTTGCCTTGGCGGCTAAACCTACCCGGGATTTGATGGGGCGAATTACCTGGTAGAGGTG",
  "TACCTATGTTGCCTTGGCGGCTAAACCTACC",
  "CGGGATTTGATGGCGAATTACCTGGTATTTTAGCCCACTTACCCGGTACCATGAGGTG",
  "GCGGCTAAACCTACCCGGGATTTGATGGCGAATTACCTGG",
  "GCGGCTAAACCTACCCGGGATTTGATGGCGAATTACAAAG",
  "GCGGCTAAACCTACCCGGGATTTGATGGCGAATTACAAAG",
  "GCGGCTAAACCTACCCGGGATTTGATGGCGAATTACAAAG"
)

sequences_ex_swarm <- swarm_clustering(
  dna_seq = sequences_ex
)

Re-cluster sequences of an object of class `physeq` or cluster a list of DNA sequences using SWARM