mmseqs | R Documentation |
MMseqs2 (Many-against-Many sequence searching) is a software suite to search and cluster huge protein and nucleotide sequence sets. MMseqs2 is open source GPL-licensed software (https://mmseqs.com). This function is a wrapper for the original mmseqs executable. The function clusters the genes or proteins in ortholog clusters and save the representative member of each one and its annotation.
mmseqs(
file_list,
coverage = 0.8,
identity = 0.8,
evalue = 1e-06,
n_cores,
cov_mode = 0,
cluster_mode = 0,
type
)
file_list |
Data frame with the full path to the genome files (gene or protein multi-fasta) or a gff_list object. |
coverage |
Minimun coverage (length) to cluster. |
identity |
Minimun Identity. |
evalue |
Maximun Evalue. |
n_cores |
Number of cores to use. |
cov_mode |
Coverage mode:
|
cluster_mode |
Cluster mode:
|
type |
'only with gff_list objects. Specify what kind of data you want to use: 'nucl' or 'prot' |
Return a mmseq object.
A mmseq object is a list of two elements. First contains a data.table/data.frame with four columns (Prot_genome, Prot_Prot, Genome_genome and Genome_Prot). This is the output of MMSeqs2 and described the clustering of the input genes/proteins. First column referes to the genome that contain the representative gene/protein of the cluster. Second one, is the representative protein of the cluster (i.e. the cluster name). Third colum is the genome that contains the gene/protein of the fourth column.
In the second element we can find a data.frame/data.table with the original annotation of all representative gene/protein of each cluster in two columns. The first one Prot_prot is the same that the second one of the first element.
Steinegger M and Soeding J. MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets. Nature Biotechnology, doi: 10.1038/nbt.3988 (2017).
Steinegger M and Soeding J. Clustering huge protein sequence sets in linear time. Nature Communications, doi: 10.1038/s41467-018-04964-5 (2018).
Mirdita M, Steinegger M and Soeding J. MMseqs2 desktop and local web server app for fast, interactive sequence searches. Bioinformatics, doi: 10.1093/bioinformatics/bty1057 (2019)
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