### Run GTDB-Tk test with specified CPUs

Source: https://ecogenomics.github.io/GTDBTk/commands/test.html

Example of how to execute the `gtdbtk test` command, specifying an output directory and the number of CPUs to use. This is useful for testing your installation with a specific configuration.

```bash
gtdbtk test --out_dir /tmp/test --cpus 3
```

--------------------------------

### GTDB-Tk check_install Example Output

Source: https://ecogenomics.github.io/GTDBTk/commands/check_install.html

This is an example output from the gtdbtk check_install command, showing the verification process for third-party software and reference data integrity.

```text
[2025-08-05 17:02:59] INFO: GTDB-Tk v2.5.0
[2025-08-05 17:02:59] INFO: gtdbtk check_install
[2025-08-05 17:02:59] INFO: Using GTDB-Tk reference data version r226: /release226
[2025-08-05 17:02:59] INFO: Running install verification
[2025-08-05 17:02:59] INFO: Checking that all third-party software are on the system path:
[2025-08-05 17:02:59] INFO:          |-- FastTree         OK
[2025-08-05 17:02:59] INFO:          |-- FastTreeMP       OK
[2025-08-05 17:02:59] INFO:          |-- guppy            OK
[2025-08-05 17:02:59] INFO:          |-- hmmalign         OK
[2025-08-05 17:02:59] INFO:          |-- hmmsearch        OK
[2025-08-05 17:02:59] INFO:          |-- pplacer          OK
[2025-08-05 17:02:59] INFO:          |-- prodigal         OK
[2025-08-05 17:02:59] INFO:          |-- skani            OK
[2025-08-05 17:02:59] INFO: Checking integrity of reference package: /release226
[2025-08-05 17:02:59] INFO:          |-- pplacer          OK
[2025-08-05 17:02:59] INFO:          |-- masks            OK
[2025-08-05 17:03:00] INFO:          |-- markers          OK
[2025-08-05 17:03:00] INFO:          |-- radii            OK
[2025-08-05 17:03:05] INFO:          |-- msa              OK
[2025-08-05 17:03:05] INFO:          |-- metadata         OK
[2025-08-05 17:03:05] INFO:          |-- taxonomy         OK
[2025-08-05 17:06:35] INFO:          |-- skani            OK
[2025-08-05 17:06:35] INFO:          |-- mrca_red         OK
[2025-08-05 17:06:35] INFO: Done.
```

--------------------------------

### Example Output of export_msa

Source: https://ecogenomics.github.io/GTDBTk/commands/export_msa.html

This is an example of the expected output when running the export_msa command, showing informational messages and completion status.

```text
[2020-04-13 10:03:05] INFO: GTDB-Tk v1.1.0
[2020-04-13 10:03:05] INFO: gtdbtk export_msa --domain arc --output /tmp/msa.faa
[2020-04-13 10:03:05] INFO: Using GTDB-Tk reference data version r89: /release89
[2020-04-13 10:03:05] INFO: Done.

```

--------------------------------

### Decorate Command Output Example

Source: https://ecogenomics.github.io/GTDBTk/commands/decorate.html

This example shows the typical output when running the decorate command. Note that the 'DECORATE NOT YET IMPLEMENTED!' warning indicates this functionality is under development.

```bash
[2020-04-14 08:20:51] INFO: GTDB-Tk v1.1.0
[2020-04-14 08:20:51] INFO: gtdbtk decorate --input_tree input.tree --output_tree output.tree
[2020-04-14 08:20:51] INFO: Using GTDB-Tk reference data version r89: /release89
[2020-04-14 08:20:51] WARNING: DECORATE NOT YET IMPLEMENTED!
[2020-04-14 08:20:51] INFO: Done.
```

--------------------------------

### Example Mask File

Source: https://ecogenomics.github.io/GTDBTk/commands/trim_msa.html

This is an example of a mask file used for trimming MSAs. '1' indicates a column to keep, and '0' indicates a column to trim.

```text
01011

```

--------------------------------

### Example GTDB-Tk align command execution

Source: https://ecogenomics.github.io/GTDBTk/commands/align.html

This example demonstrates how to run the align command, specifying the input directory for identified markers, the output directory, and the number of CPUs to use.

```bash
gtdbtk align --identify_dir identify_output/ --out_dir align_output --cpus 3

```

--------------------------------

### Root Command Output Example

Source: https://ecogenomics.github.io/GTDBTk/commands/root.html

This is an example of the output produced by the gtdbtk root command after successfully rerooting a tree. It includes timestamps, version information, and processing steps.

```text
[2020-04-14 08:26:53] INFO: GTDB-Tk v1.1.0
[2020-04-14 08:26:53] INFO: gtdbtk root --input_tree input.tree --outgroup_taxon p__Nanoarchaeota --output_tree output.tree
[2020-04-14 08:26:53] INFO: Using GTDB-Tk reference data version r89: /release89
[2020-04-14 08:26:53] INFO: Identifying genomes from the specified outgroup.
[2020-04-14 08:26:53] INFO: Identified 101 outgroup taxa in the tree.
[2020-04-14 08:26:53] INFO: Identified 1151 ingroup taxa in the tree.
[2020-04-14 08:26:53] INFO: Outgroup is monophyletic.
[2020-04-14 08:26:53] INFO: Rerooting tree.
[2020-04-14 08:26:53] INFO: Rerooted tree written to: output.tree
[2020-04-14 08:26:53] INFO: Done.

```

--------------------------------

### FastTree Command and Output Example

Source: https://ecogenomics.github.io/GTDBTk/files/tree.log.html

This snippet shows an example of the command used to run FastTree and its initial output, including version information, alignment details, and tree-building parameters. It is useful for understanding the context in which the tree.log file is generated.

```bash
Command: FastTree -wag -gamma -log infer_out/infer/intermediate_results/gtdbtk.tree.log msa.faa
FastTree Version 2.1.10 Double precision (No SSE3)
Alignment: msa.faa
Amino acid distances: BLOSUM45 Joins: balanced Support: SH-like 1000
Search: Normal +NNI +SPR (2 rounds range 10) +ML-NNI opt-each=1
TopHits: 1.00*sqrtN close=default refresh=0.80
ML Model: Whelan-And-Goldman, CAT approximation with 20 rate categories
Read 1 sequences, 5 positions
NJ  (genome_a:0.000000000);
ME_SPR1     (genome_a:0.000000000);
```

--------------------------------

### Example Translation Table Summary

Source: https://ecogenomics.github.io/GTDBTk/files/translation_table_summary.tsv.html

This example shows the format of the translation_table_summary.tsv file, mapping genome identifiers to translation table numbers.

```text
genome_1    11
genome_2    11
genome_3    11

```

--------------------------------

### Example Input MSA

Source: https://ecogenomics.github.io/GTDBTk/commands/trim_msa.html

This is an example of an untrimmed Multiple Sequence Alignment (MSA) file in FASTA format.

```fasta
>genome_a
AKLAK

```

--------------------------------

### Example tigrfam_tophit.tsv Content

Source: https://ecogenomics.github.io/GTDBTk/files/tigrfam_tophit.tsv.html

This example shows the expected format of the tigrfam_tophit.tsv file, with columns for Gene Id and Top hits.

```text
Gene Id     Top hits (Family id,e-value,bitscore)
NC_013790.1_1006    TIGR00458,2.2e-203,672.9
NC_013790.1_1081    TIGR00631,0.0,1044.6
NC_013790.1_1122    TIGR02397,1.6e-46,156.1
NC_013790.1_119     TIGR02236,3.2e-157,519.6
NC_013790.1_1201    TIGR01302,2.8e-175,580.5
NC_013790.1_1216    TIGR00194,6e-188,623.0
NC_013790.1_1229    TIGR00337,2.3e-244,808.8
NC_013790.1_1240    TIGR00442,1.2e-126,419.9
NC_013790.1_1270    TIGR02191,1.2e-59,198.5
```

--------------------------------

### GTDB-Tk classify_wf Command Example

Source: https://ecogenomics.github.io/GTDBTk/commands/classify_wf.html

This example demonstrates how to run the GTDB-Tk classify_wf command using a batch file and specifying the number of CPUs. Ensure the batch file and output directory are correctly set up before execution.

```bash
gtdbtk classify_wf --batchfile genomes/3_batchfile.tsv --out_dir classify_wf_3_genomes --cpus 20

```

--------------------------------

### Example GTDB-Tk infer output

Source: https://ecogenomics.github.io/GTDBTk/commands/infer.html

This is an example of the log output generated by the `gtdbtk infer` command during tree inference.

```log
[2020-04-14 09:37:55] INFO: GTDB-Tk v1.1.0
[2020-04-14 09:37:55] INFO: gtdbtk infer --msa_file msa.faa --out_dir infer_out
[2020-04-14 09:37:55] INFO: Using GTDB-Tk reference data version r89: /release89
[2020-04-14 09:37:55] INFO: Inferring FastTree (WAG, +gamma, support) using a maximum of 1 CPUs.
[2020-04-14 09:37:55] INFO: FastTree version: 2.1.10
[2020-04-14 09:37:55] INFO: FastTree version: 2.1.10
[2020-04-14 09:37:55] INFO: Done.

```

--------------------------------

### Example ani_closest.tsv Content

Source: https://ecogenomics.github.io/GTDBTk/files/ani_closest.tsv.html

This example shows the expected format of the ani_closest.tsv file, including query genome, reference genome, ANI, and AF.

```text
query	reference	ani	af
genome_1	GCF_000024185.1	100.0	1.0
genome_2	GCA_002498365.1	99.1599	0.94
genome_3	GCA_002498365.1	95.331	0.87

```

--------------------------------

### Example RED Values for Taxonomic Ranks

Source: https://ecogenomics.github.io/GTDBTk/files/red_dictionary.tsv.html

This example shows the typical format of the red_dictionary.tsv file, listing median RED values for different taxonomic levels.

```text
Phylum      0.187145401902
Class       0.31012292886
Order       0.514210607301
Family      0.720555789247
Genus       0.905316996783

```

--------------------------------

### Install GTDB-Tk via pip

Source: https://ecogenomics.github.io/GTDBTk/installing/pip.html

Use this command to install the latest version of GTDB-Tk. It is recommended to do this within a virtual environment.

```bash
python -m pip install gtdbtk
```

--------------------------------

### Example Output Log

Source: https://ecogenomics.github.io/GTDBTk/commands/trim_msa.html

This log output shows the execution details of the trim_msa command, including version information and the command used.

```log
[2020-04-13 10:25:13] INFO: GTDB-Tk v1.1.0
[2020-04-13 10:25:13] INFO: gtdbtk trim_msa --untrimmed_msa msa.faa --output msa_trim.faa --mask_file mask.txt
[2020-04-13 10:25:13] INFO: Using GTDB-Tk reference data version r89: /release89
[2020-04-13 10:25:13] INFO: Done.

```

--------------------------------

### Newick Format Tree Example

Source: https://ecogenomics.github.io/GTDBTk/files/classify.tree.html

This is an example of a reference tree in Newick format. It shows the phylogenetic placement of query genomes.

```plaintext
((((((((((((((((((((((GB_GCA_002498125.1:0.17454,UBA10207:0.18672)"1.0:g__UBA52...
```

--------------------------------

### Example GTDB-Tk Directory Structure

Source: https://ecogenomics.github.io/GTDBTk/installing/docker.html

Illustrates the expected directory structure for input genomes within the GTDB-Tk I/O directory on the host machine.

```bash
/host/gtdbtk_io/genomes/genome_a.fna
/host/gtdbtk_io/genomes/genome_b.fna

```

--------------------------------

### MSA FASTA Example

Source: https://ecogenomics.github.io/GTDBTk/files/msa.fasta.html

Example of a FASTA file entry containing an MSA. Each sequence is preceded by a header line including taxonomic information.

```fasta
>GB_GCA_000011125.1 d__Archaea;p__Crenarchaeota;c__Thermoprotei;o__Desulfurococcales;f__Acidilobaceae;g__Aeropyrum;s__Aeropyrum pernix
RRTSRIVLDAIAMESIVLMYKSAPTLGSIEMVERLAIEAAQGDLNAARKAPKIAVLEGIDDGRWKVKLRNEKSVLSPQTLIIIYLLELEELFKHVFLGTVVRKKYMMVARRAKAGDVQLFFKIVVKSVALKSRPAEK...

```

--------------------------------

### Example markers_summary.tsv Content

Source: https://ecogenomics.github.io/GTDBTk/files/markers_summary.tsv.html

This example demonstrates the structure and content of a markers_summary.tsv file, showing counts and lists of unique, multiple, and missing marker genes for different genomes.

```tsv
name	number_unique_genes	number_multiple_genes	number_multiple_unique_genes	number_missing_genes	list_unique_genes	list_multiple_genes	list_multiple_unique_genes	list_missing_genes
genome_1	120	2	0	0	PF00368.13,PF00410.14,PF00466.15,PF00687.16,PF00827.12,PF00900.15,PF01000.21,PF01015.13,PF01090.14,PF01092.14,PF01157.13,PF01191.14,PF01194.12,PF01198.14,PF01200.13,PF01269.12,PF01280.15,PF01282.14,PF01496.14,PF01655.13,PF01798.13,PF01864.12,PF01866.12,PF01868.11,PF01984.15,PF01990.12,PF02006.11,PF02978.14,PF03874.11,PF04019.7,PF04104.9,PF07541.7,PF13656.1,PF13685.1,TIGR00021,TIGR00037,TIGR00042,TIGR00064,TIGR00111,TIGR00134,TIGR00240,TIGR00264,TIGR00270,TIGR00279,TIGR00283,TIGR00291,TIGR00293,TIGR00307,TIGR00308,TIGR00323,TIGR00324,TIGR00335,TIGR00336,TIGR00337,TIGR00373,TIGR00389,TIGR00392,TIGR00398,TIGR00405,TIGR00408,TIGR00422,TIGR00425,TIGR00432,TIGR00442,TIGR00448,TIGR00456,TIGR00458,TIGR00463,TIGR00468,TIGR00471,TIGR00491,TIGR00501,TIGR00521,TIGR00522,TIGR00549,TIGR00658,TIGR00670,TIGR00729,TIGR00936,TIGR00982,TIGR01008,TIGR01012,TIGR01018,TIGR01020,TIGR01025,TIGR01028,TIGR01038,TIGR01046,TIGR01052,TIGR01060,TIGR01077,TIGR01080,TIGR01213,TIGR01309,TIGR01952,TIGR02076,TIGR02153,TIGR02236,TIGR02258,TIGR02338,TIGR02389,TIGR02390,TIGR02651,TIGR03626,TIGR03627,TIGR03628,TIGR03629,TIGR03636,TIGR03653,TIGR03665,TIGR03670,TIGR03671,TIGR03672,TIGR03673,TIGR03674,TIGR03677,TIGR03680,TIGR03683,TIGR03684,TIGR03722	PF04919.7,TIGR00490		
genome_2	108	1	0	13	PF00368.13,PF00410.14,PF00687.16,PF00827.12,PF00900.15,PF01000.21,PF01015.13,PF01090.14,PF01092.14,PF01157.13,PF01191.14,PF01198.14,PF01200.13,PF01269.12,PF01280.15,PF01282.14,PF01496.14,PF01655.13,PF01798.13,PF01864.12,PF01868.11,PF01984.15,PF01990.12,PF02978.14,PF03874.11,PF04019.7,PF04919.7,PF07541.7,PF13656.1,PF13685.1,TIGR00021,TIGR00037,TIGR00042,TIGR00064,TIGR00111,TIGR00134,TIGR00240,TIGR00264,TIGR00270,TIGR00279,TIGR00283,TIGR00291,TIGR00293,TIGR00307,TIGR00308,TIGR00323,TIGR00324,TIGR00335,TIGR00336,TIGR00389,TIGR00392,TIGR00398,TIGR00405,TIGR00408,TIGR00422,TIGR00425,TIGR00442,TIGR00448,TIGR00456,TIGR00463,TIGR00468,TIGR00471,TIGR00490,TIGR00491,TIGR00501,TIGR00521,TIGR00522,TIGR00658,TIGR00670,TIGR00729,TIGR00982,TIGR01008,TIGR01012,TIGR01018,TIGR01020,TIGR01025,TIGR01028,TIGR01038,TIGR01046,TIGR01052,TIGR01060,TIGR01077,TIGR01080,TIGR01213,TIGR01309,TIGR01952,TIGR02076,TIGR02153,TIGR02236,TIGR02258,TIGR02338,TIGR02389,TIGR02651,TIGR03626,TIGR03627,TIGR03628,TIGR03629,TIGR03653,TIGR03665,TIGR03670,TIGR03671,TIGR03672,TIGR03673,TIGR03674,TIGR03677,TIGR03680,TIGR03684,TIGR03722	PF01866.12	PF00466.15,PF01194.12,PF02006.11,PF04104.9,TIGR00337,TIGR00373,TIGR00432,TIGR00458,TIGR00549,TIGR00936,TIGR02390,TIGR03636,TIGR03683
genome_3	92	8	0	22	PF00410.14,PF00466.15,PF00687.16,PF00827.12,PF00900.15,PF01000.21,PF01090.14,PF01092.14,PF01157.13,PF01191.14,PF01194.12,PF01200.13,PF01269.12,PF01282.14,PF01496.14,PF01798.13,PF01864.12,PF01984.15,PF01990.12,PF02006.11,PF03874.11,PF04019.7,PF04104.9,PF04919.7,PF07541.7,TIGR00021,TIGR00037,TIGR00042,TIGR00064,TIGR00134,TIGR00240,TIGR00264,TIGR00270,TIGR00279,TIGR00283,TIGR00291,TIGR00293,TIGR00307,TIGR00308,TIGR00323,TIGR00324,TIGR00335,TIGR00336,TIGR00405,TIGR00408,TIGR00422,TIGR00425,TIGR00432,TIGR00448,TIGR00456,TIGR00463,TIGR00471,TIGR00490,TIGR00491,TIGR00501,TIGR00521,TIGR00522,TIGR00549,TIGR00658,TIGR00670,TIGR00729,TIGR00936,TIGR00982,TIGR01012,TIGR01018,TIGR01028,TIGR01038,TIGR01046,TIGR01060,TIGR01077,TIGR01080,TIGR01213,TIGR01952,TIGR02076,TIGR02153,TIGR02236,TIGR02338,TIGR02389,TIGR02390,TIGR03626,TIGR03627,TIGR03629,TIGR03653,TIGR03665,TIGR03670,TIGR03671,TIGR03672,TIGR03673,TIGR03677,TIGR03680,TIGR03684,TIGR03722	PF00368.13,PF01198.14,PF01866.12,PF13656.1,TIGR00392,TIGR01052,TIGR02651,TIGR03674		PF01015.13,PF01280.15,PF01655.13,PF01868.11,PF02978.14,PF13685.1,TIGR00111,TIGR00337,TIGR00373,TIGR00389,TIGR00398,TIGR00442,TIGR00458,TIGR00468,TIGR01008,TIGR01020,TIGR01025,TIGR01309,TIGR02258,TIGR03628,TIGR03636,TIGR03683
```

--------------------------------

### Check GTDB-Tk Installation

Source: https://ecogenomics.github.io/GTDBTk/commands/check_install.html

Run this command to verify the integrity of the GTDB-Tk reference data and check for necessary third-party software. Inconsistencies will be reported.

```bash
gtdbtk check_install
```

--------------------------------

### Display GTDB-Tk Help

Source: https://ecogenomics.github.io/GTDBTk/index.html

Access the main help documentation for GTDB-Tk commands. Use this to get an overview of available commands and their general usage.

```bash
gtdbtk -h
```

--------------------------------

### Example tree.mapping.tsv Content

Source: https://ecogenomics.github.io/GTDBTk/files/tree.mapping.tsv.html

This example shows the structure of the tree.mapping.tsv file, including genome identifiers, ANI classification status, the mapped class tree, and the classification rule.

```text
user_genome is_ani_classification   class_tree_mapped       classification_rule
3300006853_26       False   5       Rule 3

```

--------------------------------

### ANI Summary TSV Example

Source: https://ecogenomics.github.io/GTDBTk/files/ani_summary.tsv.html

This example shows the expected format of the ani_summary.tsv file, including query, reference, ANI, and AF columns. Note that 'no result' may appear if no matches are found.

```text
query	reference	ani	af
genome_1	GCF_000024185.1	100.0	1.0
genome_1	GCA_900321995.1	80.9023	0.7
genome_1	GCF_900114585.1	79.96	0.55
genome_1	GCA_900314635.1	78.4474	0.3
genome_1	GCF_900016785.1	74.6579	0.27
genome_1	GCF_000090965.1	74.7879	0.25
genome_1	GCF_000621965.1	75.8207	0.22
genome_2	GCA_002498365.1	99.1599	0.94
genome_2	GCA_002505345.1	89.9225	0.89
```

--------------------------------

### pplacer.domain.json Output Example

Source: https://ecogenomics.github.io/GTDBTk/files/pplacer.domain.json.html

This JSON structure represents the output of the pplacer tool. It includes the phylogenetic tree, detailed placement information for samples, associated metadata such as the invocation command, and the version of the output format.

```json
{
  "tree":
  "((((((((((((((((((((((GB_GCA_002498125.1:0.17454{0}, ...",
  "placements":
  [
    {"p": [[0.00110044638583, 1579, 1, -3185321.84798, 0.00140069377318]],
      "nm": [["genome_2", 1]]
    },
    {"p": [[5.05004882812e-06, 1849, 1, -3541277.48905, 6.11351501465e-06]],
      "nm": [["genome_1", 1]]
    },
    {"p": [[0.00694927704923, 1579, 1, -2665208.65502, 0.0230770193005]],
      "nm": [["genome_3", 1]]
    }
  ], "metadata":
  {"invocation":
    "pplacer -m WAG -j 3 -c \/release89\/pplacer\/gtdb_r89_ar53.refpkg -o classify_output\/classify\/intermediate_results\/pplacer\/pplacer.ar53.json align_output\/align\/gtdbtk.ar53.user_msa.fasta"
  }, "version": 3, "fields":
  ["distal_length", "edge_num", "like_weight_ratio", "likelihood",
    "pendant_length"
  ]
}
```

--------------------------------

### GTDB-Tk Classify Example

Source: https://ecogenomics.github.io/GTDBTk/commands/classify.html

An example of how to run the gtdbtk classify command using a batch file for genome input, specifying alignment and output directories, and setting the number of CPUs. This demonstrates a typical workflow for classifying multiple genomes.

```bash
gtdbtk classify --batchfile genomes/3_batchfile.tsv --align_dir 3_align/ --out_dir 3_classify --cpus 50

```

--------------------------------

### Example classification_pplacer.tsv Content

Source: https://ecogenomics.github.io/GTDBTk/files/classification_pplacer.tsv.html

This snippet shows the expected format of the classification_pplacer.tsv file, with each line representing a genome and its assigned taxonomic lineage.

```text
genome_2	d__Archaea;p__Thermoplasmatota;c__Thermoplasmata;o__Methanomassiliicoccales;f__Methanomethylophilaceae;g__VadinCA11;s__
genome_3	d__Archaea;p__Thermoplasmatota;c__Thermoplasmata;o__Methanomassiliicoccales;f__Methanomethylophilaceae;g__VadinCA11;s__
genome_1	d__Archaea;p__Euryarchaeota;c__Methanobacteria;o__Methanobacteriales;f__Methanobacteriaceae;g__Methanobrevibacter;s__

```

--------------------------------

### Tigrfam TSV Output Example

Source: https://ecogenomics.github.io/GTDBTk/files/tigrfam.tsv.html

This example shows the structure of the tigrfam.tsv file, detailing target names, accessions, query information, and domain-specific scores. It is produced by the 'identify' and 'classify_wf' tools.

```tsv
#                                                               --- full sequence ---- --- best 1 domain ---- --- domain number estimation ----
# target name        accession  query name           accession    E-value  score  bias   E-value  score  bias   exp reg clu  ov env dom rep inc description of target
#------------------- ---------- -------------------- ---------- --------- ------ ----- --------- ------ -----   --- --- --- --- --- --- --- --- --------------------- 
# NC_013790.1_950      -          TIGR00021            TIGR00021      3e-82  272.2   0.5   3.4e-82  272.0   0.5   1.0   1   0   0   1   1   1   1 # 1219054 # 1219722 # 1 # ID=1_950;partial=00;start_type=ATG;rbs_motif=None;rbs_spacer=None;gc_cont=0.383
# NC_013790.1_1725     -          TIGR00037            TIGR00037    8.2e-50  165.0   0.7   9.2e-50  164.8   0.7   1.0   1   0   0   1   1   1   1 # 2252948 # 2253355 # -1 # ID=1_1725;partial=00;start_type=ATG;rbs_motif=GGAG/GAGG;rbs_spacer=5-10bp;gc_cont=0.348
# NC_013790.1_2080     -          TIGR00042            TIGR00042    4.4e-67  222.0   0.0   4.9e-67  221.8   0.0   1.0   1   0   0   1   1   1   1 # 2740928 # 2741485 # -1 # ID=1_2080;partial=00;start_type=ATG;rbs_motif=None;rbs_spacer=None;gc_cont=0.360
# NC_013790.1_400      -          TIGR00064            TIGR00064   7.6e-102  337.2   5.8  7.6e-102  337.2   5.8   3.4   2   1   2   4   4   1   1 # 571391 # 573106 # 1 # ID=1_400;partial=00;start_type=TTG;rbs_motif=GGA/GAG/AGG;rbs_spacer=5-10bp;gc_cont=0.382
```

--------------------------------

### Prodigal Translation Table Example

Source: https://ecogenomics.github.io/GTDBTk/files/prodigal_translation_table.tsv.html

This example shows the typical output format for a Prodigal translation table summary. It lists the best translation table identified and the coding density for different tables.

```plaintext
best_translation_table      11
coding_density_4    78.38
coding_density_11   78.07

```

--------------------------------

### Download Test Genomes with GTDB-Tk

Source: https://ecogenomics.github.io/GTDBTk/examples/classify_wf.html

This snippet downloads two reference genomes and prepares the directory structure for GTDB-Tk processing. Ensure you have wget installed.

```bash
# Create the directory.
!mkdir -p /tmp/gtdbtk && cd /tmp/gtdbtk

# Obtain the genomes.
!mkdir -p /tmp/gtdbtk/genomes
!wget -q https://ftp.ncbi.nlm.nih.gov/genomes/all/GCF/003/947/435/GCF_003947435.1_ASM394743v1/GCF_003947435.1_ASM394743v1_genomic.fna.gz -O /tmp/gtdbtk/genomes/genome_a.fna.gz
!wget -q https://ftp.ncbi.nlm.nih.gov/genomes/all/GCA/002/011/125/GCA_002011125.1_ASM201112v1/GCA_002011125.1_ASM201112v1_genomic.fna.gz -O /tmp/gtdbtk/genomes/genome_b.fna.gz
```

--------------------------------

### GTDB-Tk align command output log

Source: https://ecogenomics.github.io/GTDBTk/commands/align.html

This is an example log output from the GTDB-Tk align command, showing the progress and details of the alignment process, including version information, input parameters, and processing steps.

```log
[2022-04-11 11:59:14] INFO: GTDB-Tk v2.0.0
[2022-04-11 11:59:14] INFO: gtdbtk align --identify_dir /tmp/gtdbtk/identify --out_dir /tmp/gtdbtk/align --cpus 2
[2022-04-11 11:59:14] INFO: Using GTDB-Tk reference data version r207: /srv/db/gtdbtk/official/release207
[2022-04-11 11:59:15] INFO: Aligning markers in 3 genomes with 2 CPUs.
[2022-04-11 11:59:16] INFO: Processing 3 genomes identified as archaeal.
[2022-04-11 11:59:16] INFO: Read concatenated alignment for 3,412 GTDB genomes.
[2022-04-11 11:59:16] TASK: Generating concatenated alignment for each marker.
[2022-04-11 11:59:16] INFO: Completed 3 genomes in 0.01 seconds (139.73 genomes/second).
[2022-04-11 11:59:16] TASK: Aligning 52 identified markers using hmmalign 3.1b2 (February 2015).
[2022-04-11 11:59:17] INFO: Completed 52 markers in 0.86 seconds (60.66 markers/second).
[2022-04-11 11:59:17] TASK: Masking columns of archaeal multiple sequence alignment using canonical mask.
[2022-04-11 11:59:21] INFO: Completed 3,414 sequences in 4.19 seconds (815.22 sequences/second).
[2022-04-11 11:59:21] INFO: Masked archaeal alignment from 13,540 to 10,153 AAs.
[2022-04-11 11:59:21] INFO: 0 archaeal user genomes have amino acids in <10.0% of columns in filtered MSA.
[2022-04-11 11:59:21] INFO: Creating concatenated alignment for 3,414 archaeal GTDB and user genomes.
[2022-04-11 11:59:23] INFO: Creating concatenated alignment for 3 archaeal user genomes.
[2022-04-11 11:59:23] INFO: Done.

```

--------------------------------

### Prodigal Protein FAA Output Example

Source: https://ecogenomics.github.io/GTDBTk/files/protein.faa.html

This FASTA formatted output represents predicted protein sequences. Each record starts with a header containing sequence ID, genomic coordinates, strand, and gene-specific details, followed by the amino acid sequence.

```fasta
>NC_013790.1_11 # 13256 # 14119 # -1 # ID=1_11;partial=00;start_type=ATG;rbs_motif=GGA/GAG/AGG;rbs_spacer=5-10bp;gc_cont=0.376
MKIKIAVPSKGRISEPSIKILEKAGLGLKDSTNRKLFSSTYNENIDVMFARAADIPEFVD
EGICDMGISGYDLIEEAGADVKILTDLQFGATKLVLASPENSEINTKDDLKDGMTIATEF
PNLTRKYLEENNLNIKIVKLTGSTEIAPFIGIADAITDLTSTGTTLNMNHLKIVDVILES
SIKLIANKNSYTEKNNLVEAVSTSIQGVLEAERKKLVMMNVAKENLCEVQKVMPAMSGPT
ISQVLSEEETMAVQAVVGEDEVFDLVNKLRNAGARDILVVPIERIIO*
>NC_013790.1_12 # 14771 # 14974 # 1 # ID=1_12;partial=00;start_type=ATG;rbs_motif=AGGAG;rbs_spacer=5-10bp;gc_cont=0.373
MSIPVAPIGRIIKDAGAERVSEDAKKELNAYVTAQAEAVAKKAIEFAAMAKRKTVKAEDI
ELAIKNL*
>NC_013790.1_13 # 15320 # 16339 # 1 # ID=1_13;partial=00;start_type=ATG;rbs_motif=GGA/GAG/AGG;rbs_spacer=5-10bp;gc_cont=0.354
MGRRKKQDSTLDSYFPDSDLIEEKKKKDEACKICGNPIEDATFQRCRKCLNKLALIDDLR
ELLEYVSPGESFREIDLINKGFKSLKLNILISKFLKEQLILINLDGLFTLNNIDFLNAFI
KKYGEKEKPLKETDYLIVRDDKSAFYIDVNNYSDYIKIRFNPRINKWQVDFFNENGLANT
KSFIDSNDANKEAIYYIKQLGVIGSSADDKKEEKSDKRLYSSHEGIYYSPSRGMWGAKVK
GYKGFKFIGHFSSEEEAYEARCKYLENKERTRQKYISEKRGLKSGLRNQSSGELIYFSKQ
KGKWIVRLKNKEGQIVNVGQFDTEEEANKAKEEFIKDNS*
>NC_013790.1_14 # 16923 # 17243 # 1 # ID=1_14;partial=00;start_type=ATG;rbs_motif=GGA/GAG/AGG;rbs_spacer=5-10bp;gc_cont=0.355
MSELKLDLVFDDYQIKRAKPARGSSVIHVNKRWIGKEVSIIPLPFDVDEKFIDETKGEDG
LYHLELAVKEIFSKTVSDRKDVGFFYLKESLLGLFFLIIEAPDIVY*
```

--------------------------------

### Example Unrooted Tree Format

Source: https://ecogenomics.github.io/GTDBTk/files/unrooted.tree.html

This is an example of the Newick format used for representing the unrooted tree. It shows a single genome with a branch length.

```plaintext
(genome_a:0.000000000);

```

--------------------------------

### Check GTDB-Tk Installation with Debugging

Source: https://ecogenomics.github.io/GTDBTk/commands/check_install.html

Enable debug mode when checking the GTDB-Tk installation to create intermediate files for debugging purposes. This is useful for troubleshooting.

```bash
gtdbtk check_install --debug
```

--------------------------------

### Example filtered.tsv Content

Source: https://ecogenomics.github.io/GTDBTk/files/filtered.tsv.html

This example shows the format of the filtered.tsv file, listing genomes and the reason for their exclusion due to insufficient amino acids in the MSA.

```text
genome_3	Insufficient number of amino acids in MSA (73.1%)
genome_2	Insufficient number of amino acids in MSA (87.1%)
genome_1	Insufficient number of amino acids in MSA (97.1%)
```

--------------------------------

### GTDB-Tk check_install Usage

Source: https://ecogenomics.github.io/GTDBTk/commands/check_install.html

This shows the general usage and available arguments for the gtdbtk check_install command, including optional arguments like --db_version and --debug.

```bash
usage: gtdbtk check_install [--db_version DB_VERSION] [--debug] [-h]
```

--------------------------------

### Decorate Tree Command Usage

Source: https://ecogenomics.github.io/GTDBTk/commands/decorate.html

This is the basic usage of the decorate command. It requires an input tree file and an output tree file.

```bash
gtdbtk decorate --input_tree input.tree --output_tree output.tree
```

--------------------------------

### List Genomes in Directory

Source: https://ecogenomics.github.io/GTDBTk/examples/classify_wf.html

This command lists the contents of the genomes directory to verify that the genomes were downloaded successfully.

```bash
!ls -l /tmp/gtdbtk/genomes
```

--------------------------------

### GTDB-Tk test command usage

Source: https://ecogenomics.github.io/GTDBTk/commands/test.html

This shows the basic usage and available arguments for the `gtdbtk test` command. Use this to understand the command's options.

```bash
usage: gtdbtk test [--out_dir OUT_DIR] [--cpus CPUS] [--debug] [-h]
```

--------------------------------

### Root Command Usage

Source: https://ecogenomics.github.io/GTDBTk/commands/root.html

This shows the general usage and available arguments for the gtdbtk root command. It includes required and optional named arguments for tree rooting.

```bash
usage: gtdbtk root --input_tree INPUT_TREE --outgroup_taxon OUTGROUP_TAXON
                   --output_tree OUTPUT_TREE
                   [--gtdbtk_classification_file GTDBTK_CLASSIFICATION_FILE]
                   [--custom_taxonomy_file CUSTOM_TAXONOMY_FILE]
                   [--tmpdir TMPDIR] [--debug] [-h]

```

--------------------------------

### Run ani_rep with Batchfile

Source: https://ecogenomics.github.io/GTDBTk/commands/ani_rep.html

Example of running the `ani_rep` command using a batch file to specify input genomes and output directory. The `-x fa` argument indicates FASTA files, and `--cpus` specifies the number of processors to use.

```bash
gtdbtk ani_rep --batchfile genomes/500_batchfile.tsv -x fa --out_dir test_ani_reps --cpus 90

```