Piro, V. C., Lindner, M. S., & Renard, B. Y. (2016). DUDes: a top-down taxonomic profiler for metagenomics. Bioinformatics, 32(15), 2272–2280. http://doi.org/10.1093/bioinformatics/btw150
Local installation
pip install https://github.com/pirovc/dudes.gitGlobal installation
conda install -c bioconda dudes
# or
pip install https://github.com/pirovc/dudes.gitdudes -s sampledata/hiseq_accuracy_k60.sam -d sampledata/arc-bac_refseq-cg_201503.npz -o sampledata/dudes_profile_output- The sample data is based on a set of bacterial whole-genome shotgun reads comprising 10 organisms (HiSeq - 10000 reads [1]). The read set was mapped with Bowtie2 [2] against the set of complete genome sequences (dudesdb_arc-bac_refseq-cg_201503).
- Download the pre-compiled database:
| Info | Date | Size | Link |
|---|---|---|---|
| Archaea + Bacteria - RefSeq Complete Genomes | 2015-03 | 13.2 GB | https://zenodo.org/record/1036748/files/dudesdb_arc-bac_refseq-cg_201503.tar.gz |
| Archaea + Bacteria - RefSeq Complete Genomes | 2017-09 | 37.7 GB | https://zenodo.org/record/1037091/files/dudesdb_arc-bac_refseq-cg_201709.tar.gz |
| Fungal + Viral - RefSeq Complete Genomes | 2017-09 | 9.5 GB | https://zenodo.org/record/1037288/files/dudesdb_fun-vir_refseq-cg_201709.tar.gz |
Unpack:
tar zxfv dudesdb_arc-bac_refseq-cg_201709.tar.gzMap your reads (fastq) with bowtie2 (any other mapper/index can be used - check -i parameter on DUDes.py):
bowtie2 -x dudesdb_arc-bac_refseq-cg_201709/arc-bac_refseq-cg_201709 --no-unal --very-fast -k 10 -1 reads.1.fq -2 reads.2.fq -S mapping_output.samRun DUDes:
dudes -s mapping_output.sam -d dudesdb_arc-bac_refseq-cg_201709/arc-bac_refseq-cg_201709.npz -o output_prefix- Download the pre-compiled dudes database:
| Info | Date | Size | Link |
|---|---|---|---|
| UniProt SwissProt + TrEMBL | 2024-01 | 6.4 GB | https://zenodo.org/records/10680335/files/dudesdb_uniprot_202401.tar.gz |
Unpack:
tar zxfv dudesdb_uniprot_202401.tar.gzMap your peptides (fasta) with diamond (any other mapper/index can be used - check -i parameter on DUDes.py):
Download and unpack Version 2024-01 for the UniProt SwissProt and TrEMBL fasta: https://ftp.ebi.ac.uk/pub/databases/uniprot/previous_releases/release-2023_05/knowledgebase/knowledgebase2023_05.tar.gz
tar zxfv knowledgebase2023_05.tar.gz knowledgebase/complete/uniprot_sprot.fasta.gz knowledgebase/complete/uniprot_trembl.fasta.gzCreate the database:
zcat knowledgebase/complete/uniprot_sprot.fasta.gz knowledgebase/complete/uniprot_trembl.fasta.gz | diamond makedb --db diamond_database.dmndMap your peptides:
diamond blastp \
-q path/to/your.fasta \
-d diamond_database.dmnd \
--fast \
--outfmt 6 qseqid sseqid slen sstart evalue \
-o mapping_output.tsvRun DUDes:
dudes -c mapping_output.tsv -d dudes_db.npz -o output_prefixIndex your reference file (.fasta) with bowtie2 (any other mapper/index can be used - check -i parameter on DUDes.py):
bowtie2-build -f references.fasta custom_dbCreate a dudes database based on the same set of references:
dudesdb -m 'av' -f references.fasta -n nodes.dmp -a names.dmp -g nucl_gb.accession2taxid -t 12 -o custom_db- Choose the parameter
-mconsidering the format of the headers in your reference sequences:-m 'av': New NCBI header [>NC_009925.1 Acaryochloris marina MBIC11017, complete genome.]-m 'gi': Old NCBI header [>gi|158333233|ref|NC_009925.1| Acaryochloris marina MBIC11017, complete genome.]-m 'up': UniProt header [>sp|Q197F8|002R_IIV3 Uncharacterized protein 002R OS=Invertebrate iridescent virus 3 OX=345201 GN=IIV3-002R PE=4 SV=1]
nodes.dmpandnames.dmpcan be obtained from: taxdump.tar.gznucl_gb.accession2taxid,nucl_wgs.accession2taxidorgi_taxid_nucl.dmp.gz(depending on your reference origin) can be obtained from here
dudes requires two main input files to perform the taxonomic analysis:
- a sequence alignment/map file (.sam file)
- a database generated by DUDesDB.py (.npz file)
dudesdb links taxonomic information and reference sequences identifiers (GI or accession.version). The input to dudesdb script should be the same set of reference sequences (or a subset with matching identifiers)** used for the index database of the mapping tool.
** It is possible to run DUDes with previously generated alignment/map files with a pre-compiled database (see above) or with a database generated from a different source/date/version from the mapping tool. DUDes' algorithm filters references (and matches) not found in DUDes database before performing the analysis. Notice that some information can be lost in this case.
$ dudes --help
usage: dudes [-h] (-s <sam_file> | -c <custom_blast_file>) -d <database_file>
[-i <sam_format>] [-t <threads>] [-x <taxid_start>]
[-m <max_read_matches>] [-a <min_reference_matches>]
[-l <last_rank>] [-b <bin_size>] [--no-normalize]
[-o <output_prefix>] [--debug]
[--debug_plots_dir DEBUG_PLOTS_DIR] [-v]
options:
-h, --help show this help message and exit
-s <sam_file> Alignment/mapping file in SAM format. DUDes does not
depend on any specific read mapper, but it requires
header information (@SQ
SN:gi|556555098|ref|NC_022650.1| LN:55956) and
mismatch information (check -i)
-c <custom_blast_file>
Alignment/mapping file in custom BLAST format. The
required columns and their order are: 'qseqid',
'sseqid', 'slen', 'sstart', 'evalue'. Additional
columns are ignored.
Example command for creating appropriate file with
diamond: 'diamond blastp -q {query_fasta} -d
{diamond_database} --outfmt 6 qseqid sseqid slen
sstart evalue'
-d <database_file> Database file (output from dudesdb [.npz])
-i <sam_format> SAM file format, ignored for custom blast files
['nm': sam file with standard cigar string plus NM
flag (NM:i:[0-9]*) for mismatches count | 'ex': just
the extended cigar string]. Default: 'nm'
-t <threads> # of threads. Default: 1
-x <taxid_start> Taxonomic Id used to start the analysis (1 = root).
Default: 1
-m <max_read_matches>
Keep reads up to this number/percentile of matches (0:
off / 0-1: percentile / >=1: match count). Default: 0
-a <min_reference_matches>
Minimum number/percentage of supporting matches to
consider the reference (0: off / 0-1: percentage /
>=1: read number). Default: 0.001
-l <last_rank> Last considered rank [superkingdom,phylum,class,order,
family,genus,species,strain]. Default: 'species'
-b <bin_size> Bin size (0-1: percentile from the lengths of all
references in the database / >=1: bp). Default: 0.25
-o <output_prefix> Output prefix. Default: STDOUT
--debug print debug info to STDERR
--debug_plots_dir DEBUG_PLOTS_DIR
path to directory for writing debug plots to.
-v show program's version number and exit
$ dudesdb --help
usage: dudesdb [-h] [-m <reference_mode>] -f [<fasta_files> ...] -g
[<ref2tax_files> ...] -n <nodes_file> [-a <names_file>]
[-o <output_prefix>] [-t <threads>] [-v]
options:
-h, --help show this help message and exit
-m <reference_mode> 'gi' uses the GI as the identifier (For headers like:
>gi|158333233|ref|NC_009925.1|) [NCBI is phasing out
sequence GI numbers in September 2016]. 'av' uses the
accession.version as the identifier (for headers like:
>NC_013791.2). 'up' uses the uniprot accession as
identifier (for headers like: >sp|Q197F8|... Default:
'av'
-f [<fasta_files> ...]
Reference fasta file(s) for header extraction only,
plain or gzipped - the same file used to generate the
read mapping index. Each sequence header '>' should
contain a identifier as defined in the reference mode.
-g [<ref2tax_files> ...]
reference id to taxid file(s):
'gi_taxid_nucl.dmp[.gz]' --> 'gi' mode,
'*.accession2taxid[.gz]' --> 'av' mode [from NCBI
taxonomy database https://ftp.ncbi.nlm.nih.gov/pub/tax
onomy/]'idmapping_selected.tab[.gz]' --> 'up' mode
[from https://ftp.expasy.org/databases/uniprot/current
_release/knowledgebase/idmapping/idmapping_selected.ta
b.gz
-n <nodes_file> nodes.dmp file [from NCBI taxonomy database
https://ftp.ncbi.nlm.nih.gov/pub/taxonomy/]
-a <names_file> names.dmp file [from NCBI taxonomy database
https://ftp.ncbi.nlm.nih.gov/pub/taxonomy/]
-o <output_prefix> Output prefix. Default: dudesdb
-t <threads> # of threads. Default: 1
-v show program's version number and exit
[1] Wood DE, Salzberg SL: Kraken: ultrafast metagenomic sequence classification using exact alignments. Genome Biology 2014, 15:R46.
[2] Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nature Methods 2012, 9(4), 357–9.