reCOGnizer

A tool for domain-based annotation with databases from the Conserved Domains Database.

• Features
• Installing reCOGnizer
• Setup the databases
• Annotation with reCOGnizer
• Output
• Other parameters
• Referencing reCOGnizer

Features

reCOGnizer performs domain-based annotation with RPS-BLAST and databases from CDD as reference.

• Reference databases currently implemented: CDD, NCBIfam, Pfam, TIGRFAM, Protein Clusters, SMART, COG and KOG.
• reCOGnizer performs multithread annotation with RPS-BLAST, significantly increasing the speed of annotation.
• After domain assignment to proteins, reCOGnizer converts CDD IDs to the IDs of the respective DBs, and obtains domain descriptions available at CDD.
• Further information is retrieved depending on the database in question:
  • NCBIfam, Pfam, TIGRFAM and Protein Clusters annotations are complemented with taxonomic classifications and EC numbers.
  • SMART annotations are complemented with SMART descriptions.
  • COG and KOG annotations are complemented with COG/KOG categories, EC numbers and KEGG Orthologs.

A detailed representation of reCOGnizer's workflow is presented in Fig. 1.

Installing reCOGnizer

To install reCOGnizer, simply run: conda install -c conda-forge -c bioconda recognizer

Setup the databases

THIS INFORMATION IS DEPRECATED SINCE RECOGNIZER 1.10. Databases are now installed automatically considering the recognizer_dwnl.timestamp file available in whatever the resources_directory folder is (by default, ~/recognizer_resources).

reCOGnizer requires the databases from CDD and other resources from multiple sources to be downloaded before running. This can be accomplished by running:

recognizer --download-resources --resources-directory resources_directory

where resources_directory is the directory where the resources will be stored.

By default (if a value is not specified), these resources will be stored in the user's home, but because of their large size, it might be preferable to specify other location.

Annotation with reCOGnizer

The simplest way to run reCOGnizer is to just specify the fasta filename and an output directory - though even the output directory is not mandatory.

recognizer -f input_file.faa -o output_directory --resources-directory resources_directory

Do note the --resources-directory argument is only necessary if the databases were/are to be downloaded to a different location other than the default (~/recognizer_resources).

Output

reCOGnizer takes a FASTA file (of aminoacids, commonly either .fasta or .faa) as input and produces two main outputs into the output directory:

• reCOGnizer_results.tsv, a table with the annotations for each protein
• cog_quantification.tsv and respective Krona representation (Fig. 2), which describes the functional landscape of the proteins in the input file

Fig. 2. Krona plot with the quantification of COGs identified in the simulated dataset used to test MOSCA and reCOGnizer. Click in the plot to see the interactive version that is outputed by reCOGnizer.

Using previously gathered taxonomic information

reCOGnizer can make use of taxonomic information by filtering Markov Models for the specific taxa of interest. This can be done by providing a file with the taxonomic information of the proteins. To simulate this, run the following commands, after installing reCOGnizer:

git clone https://github.com/iquasere/reCOGnizer.git
cd reCOGnizer/ci
recognizer -f proteomes.fasta --f UPIMAPI_results.tsv --tax-col 'Taxonomic lineage IDs (SPECIES)' --protein-id-col qseqid --species-taxids

Running reCOGnizer this way will usually obtain better results, but will likely take much longer to finish.

reCOGnizer parameters

options:
  -h, --help            show this help message and exit
  -f FILE, --file FILE  Fasta file with protein sequences for annotation
  -t THREADS, --threads THREADS
                        Number of threads for reCOGnizer to use [max available]
  --evalue EVALUE       Maximum e-value to report annotations for [1e-3]
  -o OUTPUT, --output OUTPUT
                        Output directory [reCOGnizer_results]
  -dr DOWNLOAD_RESOURCES, --download-resources DOWNLOAD_RESOURCES
                        This parameter is deprecated. Please do not use it [None]
  -rd RESOURCES_DIRECTORY, --resources-directory RESOURCES_DIRECTORY
                        Output directory for storing databases and other resources [~/recognizer_resources]
  -dbs DATABASES, --databases DATABASES
                        Databases to include in functional annotation (comma-separated) [all available]
  --custom-databases    If databases inputted were NOT produced by reCOGnizer [False]. Default databases of reCOGnizer (e.g., COG, TIGRFAM, ...) can't be used simultaneously with custom
                        databases. Use together with the '--databases' parameter.
  -mts MAX_TARGET_SEQS, --max-target-seqs MAX_TARGET_SEQS
                        Number of maximum identifications for each protein [1]
  --keep-spaces         BLAST ignores sequences IDs after the first space. This option changes all spaces to underscores to keep the full IDs.
  --no-output-sequences
                        Protein sequences from the FASTA input will be stored in their own column.
  --no-blast-info       Information from the alignment will be stored in their own columns.
  --output-rpsbproc-cols
                        Output columns obtained with RPSBPROC - 'Superfamilies', 'Sites' and 'Motifs'.
  -sd SKIP_DOWNLOADED, --skip-downloaded SKIP_DOWNLOADED
                        This parameter is deprecated. Please do not use it [None]
  --keep-intermediates  Keep intermediate annotation files generated in reCOGnizer's workflow, i.e., ASN, RPSBPROC and BLAST reports and split FASTA inputs.
  --quiet               Don't output download information, used mainly for CI.
  --debug               Print all commands running in the background, including those of rpsblast and rpsbproc.
  --test-run            This parameter is only appropriate for reCOGnizer's tests on GitHub. Should not be used.
  -v, --version         show program's version number and exit

Taxonomy Arguments:
  --tax-file TAX_FILE   File with taxonomic identification of proteins inputted (TSV). Must have one line per query, query name on first column, taxid on second.
  --protein-id-col PROTEIN_ID_COL
                        Name of column with protein headers as in supplied FASTA file [qseqid]
  --tax-col TAX_COL     Name of column with tax IDs of proteins [Taxonomic identifier (SPECIES)]
  --species-taxids      If tax col contains Tax IDs of species (required for running COG taxonomic)

Referencing reCOGnizer

If you use reCOGnizer, please cite its publication.