Graham Reference Dataset Repository

Since May 2021 we have been testing a Network File System (NFS) data mount to provide our users with some commonly used datasets in Bioinformatics and AI. This data mount is provided in an effort to better serve our users and to lower the usage on their project accounts with commonly used datasets. These datasets are mounted on /datashare/. You can explore the top directories by listing the mount:

[jshleap@gra-login1 ~]$ ls -lL /datashare/
total 152
drwxrwxr-x 9 jshleap sn_staff        4096 Jul  6 11:14 1000genomes
drwxrwxr-x 2 jshleap sn_staff       94208 Jun  4 15:30 BLASTDB
drwxrwxr-x 2 jshleap sn_staff         107 Jun  4 15:30 BLAST_FASTA
drwxrwxr-x 5 jshleap sn_staff         229 Jun  4 18:49 CIFAR-10
drwxrwxr-x 5 jshleap sn_staff         221 Jun  4 18:49 CIFAR-100
drwxrwxr-x 6 jshleap sn_staff         115 Apr 27 10:00 COCO
drwxrwxr-x 2 jshleap sn_staff         135 Jun 10 18:23 DIAMONDDB_2.0.9
drwxrwxr-x 6 jshleap sn_staff         321 Feb  4 17:39 EggNog
drwxrwxr-x 3 jshleap sn_staff          46 Mar 23 14:23 hg38
drwxrws--- 9 jshleap imagenet-optin   244 Jun 16 09:22 ImageNet
drwxrwxr-x 8 jshleap sn_staff        4096 Jun  7 16:58 kraken2_dbs
drwxrwxr-x 2 jshleap sn_staff         191 Jun  4 18:49 MNIST
drwxrwxr-x 2 jshleap sn_staff          50 Jun  4 18:51 MPI_SINTEL
drwxrwxr-x 2 jshleap sn_staff        4096 Jun  9 17:09 NCBI_taxonomy
drwxrwxr-x 6 jshleap sn_staff         145 Feb  4 22:44 PANTHER
drwxrwxr-x 5 jshleap sn_staff        4096 Apr 19 17:24 PFAM
drwxrwxr-x 7 jshleap sn_staff        4096 Mar 29 09:52 SILVA
drwxrwxr-x 6 jshleap sn_staff         257 Feb  4 22:46 SVHN
drwxrwxr-x 4 jshleap sn_staff         189 Apr 19 17:59 UNIPROT
drwxrwx--- 5 jshleap voxceleb-optin    98 Apr 23 15:15 VoxCeleb

Below a detailed description of each dataset and how to access them.

Bioinformatics

Bioinformatics software often uses reference datasets (often referred to as databases) to work properly. In [www.sharcnet.ca SHARCNET] we are providing a set of these datasets for bioinformatics:

1000 Genomes

In human genetics, the 1000 genomes project (1KGP) was an effort to catalogue human genetic variation and has become a reference and a comparison point to many studies. We provide their data from their FTP site, and will be checked for updates twice a year (June and December).

Directory structure

1000 Genomes directory tree (up to level 2):

├── CHANGELOG
├── data_collections
│   ├── 1000G_2504_high_coverage
│   ├── 1000G_2504_high_coverage_SV
│   ├── 1000_genomes_project
│   ├── gambian_genome_variation_project
│   ├── gambian_genome_variation_project_GRCh37
│   ├── geuvadis
│   ├── han_chinese_high_coverage
│   ├── HGDP
│   ├── HGSVC2
│   ├── hgsv_sv_discovery
│   ├── HLA_types
│   ├── illumina_platinum_pedigree
│   ├── index.html
│   ├── README_data_collections.md
│   └── simons_diversity_data
├── historical_data
│   ├── former_toplevel
│   ├── index.html
│   └── README_historical_data.md
├── index.html
├── phase1
│   ├── analysis_results
│   ├── data
│   ├── index.html
│   ├── phase1.alignment.index
│   ├── phase1.alignment.index.bas.gz
│   ├── phase1.exome.alignment.index
│   ├── phase1.exome.alignment.index.bas.gz
│   ├── phase1.exome.alignment.index.HsMetrics.gz
│   ├── phase1.exome.alignment.index.HsMetrics.stats
│   ├── phase1.exome.alignment.index_stats.csv
│   ├── README.phase1_alignment_data
│   └── technical
├── phase3
│   ├── 20130502.phase3.analysis.sequence.index
│   ├── 20130502.phase3.exome.alignment.index
│   ├── 20130502.phase3.low_coverage.alignment.index
│   ├── 20130502.phase3.sequence.index
│   ├── 20130725.phase3.cg_sra.index
│   ├── 20130820.phase3.cg_data_index
│   ├── 20131219.populations.tsv
│   ├── 20131219.superpopulations.tsv
│   ├── data
│   ├── index.html
│   ├── integrated_sv_map
│   ├── README_20150504_phase3_data
│   └── README_20160404_where_are_the_phase3_variants
├── pilot_data
│   ├── data
│   ├── index.html
│   ├── paper_data_sets
│   ├── pilot_data.alignment.index
│   ├── pilot_data.alignment.index.bas.gz
│   ├── pilot_data.sequence.index
│   ├── README.alignment.index
│   ├── README.bas
│   ├── README.sequence.index
│   ├── release
│   ├── SRP000031.sequence.index
│   ├── SRP000032.sequence.index
│   ├── SRP000033.sequence.index
│   └── technical
├── PRIVACY-NOTICE.txt
├── README_ebi_aspera_info.md
├── README_file_formats_and_descriptions.md
├── README_ftp_site_structure.md
├── README_missing_files.md
├── README_populations.md
├── README_using_1000genomes_cram.md
├── release
│   ├── 2008_12
│   ├── 2009_02
│   ├── 2009_04
│   ├── 2009_05
│   ├── 2009_08
│   ├── 20100804
│   ├── 2010_11
│   ├── 20101123
│   ├── 20110521
│   ├── 20130502
│   └── index.html
└── technical
    ├── browser
    ├── index.html
    ├── method_development
    ├── ncbi_varpipe_data
    ├── other_exome_alignments
    ├── other_exome_alignments.alignment_indices
    ├── phase3_EX_or_LC_only_alignment
    ├── pilot2_high_cov_GRCh37_bams
    ├── pilot3_exon_targetted_GRCh37_bams
    ├── qc
    ├── README.reference
    ├── reference
    ├── retired_reference
    ├── simulations
    ├── supporting
    └── working

As per their README, the directory structure is:

changelog_details

This directory contains a series of files detailing the changes made to the FTP site over time.

data_collections

The data_collections directory contains directories for various collections of data, typically generated by different projects. Among the data collections is the 1000 Genomes Project data.

For each collection of data, within the directory for that collection, README and index files provide information on the collection. Under each collection directory, there is a data directory, under which files are organised by population and then sample. Further information can be found in/datashare/1000genomes/data_collections/README_data_collections.md.

historical_data

This directory was created during a rearrangement of the FTP site in September 2015. It houses README and index files that were formerly present at the toplevel of this site, including dedicated index directories. Further information is available in /datashare/1000genomes/historical_data/README_historical_data.md.

phase1

This directory contains data that supports the publications associated with phase 1 of the 1000 Genomes Project.

phase3

This directory contains data that supports the publications associated with phase 3 of the 1000 Genomes Project.

pilot_data

This directory contains data that supports the publications associated with the pilot phase of the 1000 Genomes Project.

release

The release directory contains dated directories which contain analysis results sets plus README files explaining how those data sets were produced.

Originally, the date in release subdirectory names was the date on which the given release was made. Thereafter, the release subdirectory dates were based on the date in the name of the corresponding YYYYMMDD.sequence.index file. In future, the date in the directory name will be chosen in a manner appropriate to the data and the nature of the release.

Examples of release subdirectories are: - /datashare/1000genomes/release/2008_12/

In cases where release directories are named based on the date of the YYYYMMDD.sequence.index, the SNP calls, indel calls, etc. in these directories are based on alignments produced from data listed in the YYYYMMDD.sequence.index file.

For example, the directory /datashare/1000genomes/release/20100804/ contains the release versions of SNP and indel calls based on the /datashare/1000genomes/historical_data/former_toplevel/sequence_indices/20100804.sequence.index file.

technical

The technical directory contains subdirectories for other data sets such as simulations, files for method development, interim data sets, reference genomes, etc..

An example of data stored under technical is /datashare/1000genomes/datashare/1000genomes/technical/simulations/.

WARNING: /datashare/1000genomes/technical/working/
 The working directory under technical contains data that has experimental (non-public release) status
 and is suitable for internal project use only. Please use with caution.

BLASTDB

BLAST uses a standard set of BLAST databases for nucleotide, protein, and translated BLAST searches. These databases contain the sequence information deposited in the NCBI and are made available here as pre-formatted databases with the same structure as the /db directory of the BLAST ftp site.

The pre-formatted databases offer the following advantages:

• Pre-formatting removes the need to run makeblastdb
• Species-level taxonomy ids are included for each database entry
• Sequences in FASTA format can be generated from the pre-formatted databases by using the blastdbcmd utility

IMPORTANT: The BLAST databases found in this folder are version 5 (v5). Information on newly enabled features with the v5 databases can be find here.

All Pre-formatted databases available are located in Graham's /datashare/BLASTDB and will be updated every 3 months (Jan, Apr, Jul, Oct).

Directory structure

/datashare/BLASTDB contains all the pre-formatted without any subfolder. We include the Following:

Name	Type	Title
16S_ribosomal_RNA	DNA	16S ribosomal RNA (Bacteria and Archaea type strains)
18S_fungal_sequences	DNA	18S ribosomal RNA sequences (SSU) from Fungi type and reference material
28S_fungal_sequences	DNA	28S ribosomal RNA sequences (LSU) from Fungi type and reference material
Betacoronavirus	DNA	Betacoronavirus
GCF_000001405.38_top_level	DNA	Homo sapiens GRCh38.p12 [GCF_000001405.38] chromosomes plus unplaced and unlocalized scaffolds
GCF_000001635.26_top_level	DNA	Mus musculus GRCm38.p6 [GCF_000001635.26] chromosomes plus unplaced and unlocalized scaffolds
ITS_RefSeq_Fungi	DNA	Internal transcribed spacer region (ITS) from Fungi type and reference material
ITS_eukaryote_sequences	DNA	ITS eukaryote BLAST
env_nt	DNA	environmental samples
nt	DNA	Nucleotide collection (nt)
patnt	DNA	Nucleotide sequences derived from the Patent division of GenBank
pdbnt	DNA	PDB nucleotide database
ref_euk_rep_genomes	DNA	RefSeq Eukaryotic Representative Genome Database
ref_prok_rep_genomes	DNA	Refseq prokaryote representative genomes (contains refseq assembly)
ref_viroids_rep_genomes	DNA	Refseq viroids representative genomes
ref_viruses_rep_genomes	DNA	Refseq viruses representative genomes
refseq_rna	DNA	NCBI Transcript Reference Sequences
refseq_select_rna	DNA	RefSeq Select RNA sequences
env_nr	Protein	Proteins from WGS metagenomic projects (env_nr)
landmark	Protein	Landmark database for SmartBLAST
nr	Protein	All non-redundant GenBank CDS translations+PDB+SwissProt+PIR+PRF excluding environmental samples from WGS projects
pdbaa	Protein	PDB protein database
pataa	Protein	Protein sequences derived from the Patent division of GenBank
refseq_protein	Protein	NCBI Protein Reference Sequences
refseq_select_prot	Protein	RefSeq Select proteins
swissprot	Protein	Non-redundant UniProtKB/SwissProt sequences
split-cdd	Protein	CDD split into 32 volumes
tsa_nr	Protein	Transcriptome Shotgun Assembly (TSA) sequences

Usage

The most efficient way to use these databases is to copy the specific database to $SLURM_TMPDIR at the begining of your sbatch script. This will add between 5 to 30 minutes (depending on the database you are moving), so use it only when you know that your blast run will take longer than one hour. For example, your sbatch script can look something like this:

   #!/bin/bash
   #SBATCH --time=02:00:00
   #SBATCH --mem=32G
   #SBATCH --cpus-per-task=8
   #SBATCH --account=def-someuser
   module load  StdEnv/2020  gcc/9.3.0 blast+/2.11.0 # load blast and dependencies
   tar cf - /datashare/BLASTDB/nr | (cd ${SLURM_TMPDIR}; tar xvf -) && # copy the required database (in this case nr) to $SLURM_TMPDIR
   blastp -db ${SLURM_TMPDIR}/nr -num_threads ${SLURM_CPUS_PER_TASK} -query myquery.fasta

Note that the example above assumes that you have launched the job from the same directory where myquery.fasta is located, that myquery.fasta is a set of protein sequences, and that nr is required as database.

You can also use /datashare/BLASTDB/nr (as per example), but it might be slower than having the databases in the local disk.

Other Compute Canada Sources

Blast databases can also be found in all cluster through a CVMFS repository (see https://docs.computecanada.ca/wiki/Genomics_data) unfortunately, these databases are based on the cloud ftp from NCBI which is out of date.

BLAST_FASTA

This directory contains the raw sequences located in the blast/db/FASTA/ of their directory of the NCBI FTP repository in compressed (by gzip) format:

  134M Apr 10 15:36 swissprot.gz
  96G  Apr 10 22:11 nr.gz
  108G Apr 12 07:55 nt.gz
  32M  Jun  4 15:30 pdbaa.gz

Similar to the pre-formatted databases (located in /datashare/BLASTDB), these fasta files can be found at /datashare/BLAST_FASTA and will be updated every 3 months (Jan, Apr, Jul, Oct).

DIAMONDDB_2.0.9

DIAMOND is a sequence aligner for protein and translated DNA searches, designed for high performance analysis of big sequence data. It works in a similar manner than blast but it has some optimizations done both at the database level and at the software level. In SHARCNET we provide pre-formatted databases for DIAMOND v.2.0.9 built using the following:

  diamond makedb --in <(gunzip -c /datashare/BLAST_FASTA/nr.gz) -d nr --taxonmap <(gunzip -c /datashare/NCBI_taxonomy/prot.accession2taxid.FUL.gz) --taxonnodes /datashare/NCBI_taxonomy/nodes.dmp
  diamond makedb --in <(gunzip -c /datashare/BLAST_FASTA/nt.gz) -d nt --taxonmap <(gunzip -c /datashare/NCBI_taxonomy/nucl_gb.accession2taxid.gz) --taxonnodes /datashare/NCBI_taxonomy/nodes.dmp
  diamond makedb --in <(gunzip -c /datashare/BLAST_FASTA/pdbaa.gz) -d pdbaa --taxonmap <(gunzip -c /datashare/NCBI_taxonomy/pdb.accession2taxid.gz) --taxonnodes /datashare/NCBI_taxonomy/nodes.dmp
  diamond makedb --in <(gunzip -c /datashare/BLAST_FASTA/swissprot.gz) -d swissprot --taxonmap <(gunzip -c /datashare/NCBI_taxonomy/prot.accession2taxid.FULL.gz) --taxonnodes /datashare/NCBI_taxonomy/nodes.dmp

As can be seen 4 databases are distributed in the /datashare/DIAMONDDB_2.0.9 directory representing blast's nt, nr, pdbaa, and swissprot. All of them contain taxonomic information. Since the source of these databases are the BLAST_FASTA, the updates of the databases will follow the same trimonthly schedule (Jan, Apr, Jul, Oct).

Consideration when using these databases

The Diamond program uses a lot of memory and temporary disk space, especially when dealing with big databases (like the ones we have here) and large query sequences (both in length and number). Should the program fail due to running out of either one, you need to set a lower value for the block size parameter -b.

Usage

The most efficient way to use these databases is to copy the specific database to $SLURM_TMPDIR at the begining of your sbatch script, just like with BLASTDB. This will add between 5 to 30 minutes (depending on the database you are moving), so use it only when you know that your blast run will take longer than one hour. In this case, different than with BLASTDB, only one file needs to be move, which means that cp is more efficient than tar moving the file. For example, your sbatch script can look something like this:

   #!/bin/bash
   #SBATCH --time=02:00:00
   #SBATCH --mem=32G
   #SBATCH --cpus-per-task=8
   #SBATCH --account=def-someuser
   module load  StdEnv/2020  diamond/2.0.9 # load blast and dependencies
   cp /datashare/DIAMONDDB_2.0.9/nr.dmnd ${SLURM_TMPDIR} # copy the required database (in this case nr) to $SLURM_TMPDIR
   diamond blastp -d /datashare/DIAMONDDB_2.0.9/nr -q YOURREADS.fasta -o AN_OUTPUT.tsv

Note that the example above assumes that you have launched the job from the same directory where YOURREADS.fasta is located, that YOURREADS.fasta is a set of protein sequences, and that nr is required as database.

You can also use /datashare/DIAMONDDB_2.0.9/nr (as per example), but it might be slower than having the databases in the local disk.

EggNog

The EggNOG database is a database of biological information hosted by the EMBL. It is based on the original idea of COGs and expands that idea to non-supervised orthologous groups constructed from numerous organisms.

This data mount contains a copy of latest EggNogg databases

Directory structure

EggNOG directory tree (up to level 2):

├── e5.level_info.tar.gz
├── e5.og_annotations.tsv
├── e5.proteomes.faa
├── e5.sequence_aliases.tsv
├── e5.taxid_info.tsv
├── e5.viruses.faa
├── gbff
│   ├── eutils_wgs_calledGenes
│   └── eutils_wgs_calledGenes_2
├── id_mappings
│   └── uniprot
├── per_tax_level
│   ├── 1
│   ├── 10
│   ├── 1016
│   ├── 10239
│   ├── 1028384
│   ├── 10404
│   ├── 104264
│   ├── 10474
│   ├── 10477
│   ├── 1060
│   ├── 10656
│   ├── 10662
│   ├── 10699
│   ├── 10744
│   ├── 10841
│   ├── 10860
│   ├── 1090
│   ├── 1100069
│   ├── 110618
│   ├── 11157
│   ├── 1117
│   ├── 112252
│   ├── 1129
│   ├── 1142
│   ├── 1150
│   ├── 1161
│   ├── 11632
│   ├── 1164882
│   ├── 117743
│   ├── 117747
│   ├── 118882
│   ├── 118884
│   ├── 1189
│   ├── 118969
│   ├── 119043
│   ├── 119045
│   ├── 119060
│   ├── 119065
│   ├── 119066
│   ├── 119069
│   ├── 119089
│   ├── 119603
│   ├── 11989
│   ├── 121069
│   ├── 1212
│   ├── 122277
│   ├── 1224
│   ├── 1236
│   ├── 1239
│   ├── 1268
│   ├── 1283313
│   ├── 129337
│   ├── 1297
│   ├── 1303
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│   ├── 1307
│   ├── 1313
│   ├── 135613
│   ├── 135614
│   ├── 135618
│   ├── 135619
│   ├── 135623
│   ├── 135624
│   ├── 135625
│   ├── 1357
│   ├── 136841
│   ├── 136843
│   ├── 136845
│   ├── 136846
│   ├── 136849
│   ├── 1386
│   ├── 142182
│   ├── 145357
│   ├── 147541
│   ├── 147545
│   ├── 147548
│   ├── 147550
│   ├── 150247
│   ├── 1506553
│   ├── 1511857
│   ├── 155619
│   ├── 1570339
│   ├── 157897
│   ├── 1653
│   ├── 167375
│   ├── 171550
│   ├── 171551
│   ├── 1762
│   ├── 178469
│   ├── 182709
│   ├── 183925
│   ├── 183939
│   ├── 183963
│   ├── 183967
│   ├── 183968
│   ├── 183980
│   ├── 186801
│   ├── 186804
│   ├── 186806
│   ├── 186807
│   ├── 186813
│   ├── 186818
│   ├── 186820
│   ├── 186821
│   ├── 186822
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│   ├── 186824
│   ├── 186827
│   ├── 186828
│   ├── 186928
│   ├── 189330
│   ├── 189775
│   ├── 191028
│   ├── 191675
│   ├── 2
│   ├── 200643
│   ├── 200783
│   ├── 200795
│   ├── 200918
│   ├── 200930
│   ├── 200940
│   ├── 201174
│   ├── 203494
│   ├── 203682
│   ├── 203691
│   ├── 204037
│   ├── 204428
│   ├── 204432
│   ├── 204441
│   ├── 204457
│   ├── 204458
│   ├── 2063
│   ├── 206350
│   ├── 206351
│   ├── 206389
│   ├── 213113
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│   ├── 213118
│   ├── 213462
│   ├── 213481
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│   ├── 216572
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│   ├── 225057
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│   ├── 2323
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│   ├── 2433
│   ├── 244698
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│   ├── 246874
│   ├── 252301
│   ├── 252356
│   ├── 255475
│   ├── 256005
│   ├── 265
│   ├── 265975
│   ├── 267888
│   ├── 267889
│   ├── 267890
│   ├── 267893
│   ├── 267894
│   ├── 2759
│   ├── 28037
│   ├── 28211
│   ├── 28216
│   ├── 28221
│   ├── 2836
│   ├── 283735
│   ├── 285107
│   ├── 28883
│   ├── 28889
│   ├── 28890
│   ├── 289201
│   ├── 29
│   ├── 29000
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│   ├── 29258
│   ├── 29547
│   ├── 301297
│   ├── 302485
│   ├── 3041
│   ├── 308865
│   ├── 311790
│   ├── 314146
│   ├── 314294
│   ├── 31979
│   ├── 31993
│   ├── 32003
│   ├── 32061
│   ├── 32066
│   ├── 32199
│   ├── 326319
│   ├── 326457
│   ├── 33090
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│   ├── 33183
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│   ├── 33213
│   ├── 33342
│   ├── 33554
│   ├── 335928
│   ├── 33867
│   ├── 33958
│   ├── 34008
│   ├── 34037
│   ├── 34383
│   ├── 34384
│   ├── 34397
│   ├── 35237
│   ├── 35268
│   ├── 35278
│   ├── 35301
│   ├── 35325
│   ├── 35493
│   ├── 355688
│   ├── 35718
│   ├── 358033
│   ├── 363408
│   ├── 3699
│   ├── 38820
│   ├── 39782
│   ├── 400634
│   ├── 40117
│   ├── 40674
│   ├── 41294
│   ├── 414999
│   ├── 422676
│   ├── 423358
│   ├── 439488
│   ├── 43988
│   ├── 4447
│   ├── 451866
│   ├── 451867
│   ├── 451870
│   ├── 452284
│   ├── 45401
│   ├── 45404
│   ├── 45667
│   ├── 46205
│   ├── 464095
│   ├── 468
│   ├── 4751
│   ├── 4776
│   ├── 4890
│   ├── 4891
│   ├── 4893
│   ├── 5042
│   ├── 50557
│   ├── 506
│   ├── 508458
│   ├── 5125
│   ├── 5129
│   ├── 5139
│   ├── 5148
│   ├── 5151
│   ├── 52018
│   ├── 5204
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│   ├── 558415
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│   ├── 5796
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│   ├── 5863
│   ├── 5878
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│   ├── 7399
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│   ├── 74201
│   ├── 74385
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│   ├── 76804
│   ├── 76831
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│   ├── 7898
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│   ├── 82117
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│   ├── 84406
│   ├── 8459
│   ├── 84992
│   ├── 84995
│   ├── 84998
│   ├── 85004
│   ├── 85005
│   ├── 85008
│   ├── 85009
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│   ├── 85012
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│   ├── 85016
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│   ├── 85019
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│   ├── 85021
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│   ├── 85026
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│   ├── 909932
│   ├── 91061
│   ├── 91561
│   ├── 91835
│   ├── 9263
│   ├── 92860
│   ├── 93682
│   ├── 9397
│   ├── 9443
│   ├── 9604
│   ├── 97050
│   ├── 976
│   ├── 995019
│   └── 9989
└── raw_data
    ├── e5.best_hit_homology_matrix.tsv.gz
    └── speciation_events.tsv.gz

386 directories, 8 files

The top level directory includes the e5 release of the proteomes and its annotations. The gbff folder contain annotation in genebank format. The folder id_mappings contain the taxonomic information and the mappings with EggNog's taxids. In the per_tax_level contains a series of folders, labeled by taconomic ID. In each one of them, you can find *_annotations.tsv.gz *_hmms.tar *_hmms.tar.gz *_members.tsv.gz *_raw_algs.tar *_stats.tsv *_trees.tsv.gz *_trimmed_algs.tar with the Hidden Markov models alignments, annotations, profiles, and phylogenetic trees. Finally, the folder raw_data contains the homology/speciation events used in EggNog's clustering.

NCBI_taxonomy

This dataset contains the NCBI taxonomy ftp. Is intended to work with multiple software (seqkit, kraken, blast, diamond, etc) as well as with direct search of accession numbers, taxonomic IDs and related information. It will be updated with the blast databases.

Directory structure

NCBI_taxonomy directory tree (up to level 2):

── accession2taxid
├── Ccode_dump.txt
├── citations.dmp
├── coll_dump.txt
├── Collection_codes.txt
├── Cowner_dump.txt
├── dead_nucl.accession2taxid.gz
├── dead_nucl.accession2taxid.gz.md5
├── dead_prot.accession2taxid.gz
├── dead_prot.accession2taxid.gz.md5
├── dead_wgs.accession2taxid.gz
├── dead_wgs.accession2taxid.gz.md5
├── delnodes.dmp
├── division.dmp
├── gc.prt
├── gencode.dmp
├── gi_taxid_nucl.dmp.gz
├── gi_taxid_nucl.dmp.gz.md5
├── gi_taxid_prot.dmp.gz
├── gi_taxid_prot.dmp.gz.md5
├── gi_taxid.readme
├── Icode_dump.txt
├── Institution_codes.txt
├── merged.dmp
├── names.dmp
├── ncbi_taxonomy_genussp.txt
├── new_taxdump.tar.gz
├── new_taxdump.tar.gz.md5
├── new_taxdump.tar.Z
├── new_taxdump.tar.Z.md5
├── new_taxdump.zip.md5
├── nodes.dmp
├── nucl_gb.accession2taxid.gz
├── nucl_gb.accession2taxid.gz.md5
├── nucl_wgs.accession2taxid.gz
├── nucl_wgs.accession2taxid.gz.md5
├── pdb.accession2taxid.gz
├── pdb.accession2taxid.gz.md5
├── prot.accession2taxid.FULL.gz
├── prot.accession2taxid.FULL.gz.md5
├── prot.accession2taxid.gz
├── prot.accession2taxid.gz.md5
├── readme.txt
├── taxcat_readme.txt
├── taxcat.tar.gz
├── taxcat.tar.gz.md5
├── taxcat.tar.Z
├── taxcat.tar.Z.md5
├── taxcat.zip.md5
├── taxdmp.zip.md5
├── taxdump_readme.txt
├── taxdump.tar.gz
├── taxdump.tar.gz.md5
├── taxdump.tar.Z
├── taxdump.tar.Z.md5
└── Unique_institution_codes.txt

0 directories, 56 files