| Name | GOTTCHA2 JSON |
| Version |
2.1.8.55
JSON |
| download |
| home_page | |
| Summary | Genomic Origin Through Taxonomic CHAllenge (GOTTCHA) v2 |
| upload_time | 2024-02-09 21:01:55 |
| maintainer | |
| docs_url | None |
| author | |
| requires_python | |
| license | Copyright (2019). TRIAD National Security, LLC. This material was produced under U.S. Government contract DE-AC52-06NA25396 for Los Alamos National Laboratory (LANL), which is operated by Los Alamos National Security, LLC for the U.S. Department of Energy. The U.S. Government has rights to use, reproduce, and distribute this software. NEITHER THE GOVERNMENT NOR TRIAD National Security, LLC MAKES ANY WARRANTY, EXPRESS OR IMPLIED, OR ASSUMES ANY LIABILITY FOR THE USE OF THIS SOFTWARE. If software is modified to produce derivative works, such modified software should be clearly marked, so as not to confuse it with the version available from LANL. Additionally, this program is free software; you can redistribute it and/or modify it under the terms of the BSD 3-clause License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. Accordingly, this program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY (without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE). See the GNU General Public License for more details. |
| keywords |
bioinformatics
taxonomy
profiler
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
[](https://gottcha2.readthedocs.io/en/latest/_images/gottcha_icon.png)
# Genomic Origin Through Taxonomic CHAllenge (GOTTCHA)
[](https://github.com/poeli/GOTTCHA2/actions?query=workflow%3Agottcha)
GOTTCHA is an application of a novel, gene-independent and signature-based metagenomic taxonomic profiling
method with significantly smaller false discovery rates (FDR) that is laptop deployable. Our algorithm was
tested and validated on twenty synthetic and mock datasets ranging in community composition and complexity,
was applied successfully to data generated from spiked environmental and clinical samples, and robustly
demonstrates superior performance compared with other available tools.
GOTTCHAv2 is currently under development in BETA stage. Pre-built databases for v1 are incompatible with v2.
-------------------------------------------------------------------
## DEPENDENCIES
GOTTCHA2 profiler is written in Python3 and leverage minimap2 to map reads to signature sequences. In order to run GOTTCHA2 correctly, your system requires to have following dependencies installed correctly. The YAML file for Conda environment can be found in `environment.yml`.
- Python 3.4+
- minimap2 2.1+
- pandas
- samtools
-------------------------------------------------------------------
## QUICK START
1. Download or git clone GOTTCHA2 from this repository and `cd` to the cloned directory.
2. Run `pip install .`
2. Download the latest version of the GOTTCHA2 database. (This step may take some time)
https://ref-db.edgebioinformatics.org/gottcha2/RefSeq-r220/
3. Run GOTTCHA2:
$ gottcha2.py -d RefSeq-r220_BAVxH-cg/gottcha_db.species.fna -t 8 -i <FASTQ>
OR
$ gottcha2 profile -d RefSeq-r220_BAVxH-cg/gottcha_db.species.fna -t 8 -i <FASTQ>
-------------------------------------------------------------------
## RESULT
GOTTCHA2 can output the profiling results in either CSV, TSV or BIOM format.
- summary (.tsv or .csv) - A summary of profiling results (10 columns) in taxonomic ranks breakdown
- full (.tsv or .csv) - A full profiling results including unfiltered profiling results and additional columns
- lineage (.lineage.tsv or .lineage.tsv) - output lineage and abundance of the profiled taxon per line
- extract (.extract[TAXID].fastq) - Extracted reads for a specific taxon.
#### Summary and full reports
A full GOTTCHA2 report has 22 columns in tab-delimited format. The summary report is a brief version that has the first 10 columns and qualified taxonomies. The report lists profiling results at taxonomic rank breakdown from superkingdom to strain, following by other information listed below. The rollup depth of coverage (ROLLUP_DOC) is used to calculate relative abundance (column 10) by default, as well as other relative abundance calculations (column 19-21).
| COLUMN | NAME | DESCRIPTION | NOTE |
|--------|-----------------------|----------------------------------------------------------------------------|------------------------------------------------------------|
| 1 | LEVEL | Taxonomic rank | |
| 2 | NAME | Taxonomic name | |
| 3 | TAXID | Taxonomic ID | |
| 4 | READ_COUNT | Number of mapped reads | |
| 5 | TOTAL_BP_MAPPED | Total bases of mapped reads | |
| 6 | TOTAL_BP_MISMATCH | Total mismatch bases of mapped reads | |
| 7 | LINEAR_LENGTH | Number of non-overlapping bases covering the signatures | |
| 8 | LINEAR_DOC | Linear depth-of-coverage | = TOTAL_BP_MAPPED / LINEAR_LENGTH |
| 9 | ROLLUP_DOC | Rollup depth-of-coverage | = ∑ DOC of sub-level |
| 10 | REL_ABUNDANCE | Relative abundance (normalized abundance) | = ABUNDANCE / ∑ ABUNDANCE of given level |
| 11 | LINEAR_COV | Proportion of covered signatures to total signatures of mapped organism(s) | = LINEAR_LENGTH / SIG_LENGTH_TOL |
| 12 | LINEAR_COV_MAPPED_SIG | Proportion of covered signatures to mapped signatures | = LINEAR_LENGTH / SIG_LENGTH_MAPPED |
| 13 | BEST_LINEAR_COV | Best linear coverage of corresponding taxons | |
| 14 | DOC | Average depth-of-coverage | = TOTAL_BP_MAPPED / SIG_LENGTH_TOL |
| 15 | BEST_DOC | Best DOC of corresponding taxons | |
| 16 | SIG_LENGTH_TOL | Length of all signatures in mapped organism(s) | |
| 17 | SIG_LENGTH_MAPPED | Length of signatures in mapped signature fragment(s) | |
| 18 | ABUNDANCE | abundance of the taxon | value of either ROLLUP_DOC, READ_COUNT or TOTAL_BP_MAPPED |
| 19 | ZSCORE | Estimated Z-score of depth of coverage of the mapped region | |
| 20 | NOTE | Only note the reason for being filtered out | |
-------------------------------------------------------------------
## USAGE
```
usage: gottcha2.py [-h] [-i [FASTQ] [[FASTQ] ...]] [-s [SAMFILE]]
[-d [MINIMAP2_INDEX]] [-l [LEVEL]] [-ti [FILE]] [-np]
[-pm <INT>] [-e [TAXID]] [-fm [STR]] [-r [FIELD]]
[-t <INT>] [-o [DIR]] [-p <STR>] [-xm <STR>] [-mc <FLOAT>]
[-mr <INT>] [-ml <INT>] [-mz <FLOAT>] [-nc] [-c] [-v]
[--silent] [--debug]
Genomic Origin Through Taxonomic CHAllenge (GOTTCHA) is an annotation-
independent and signature-based metagenomic taxonomic profiling tool that has
significantly smaller FDR than other profiling tools. This program is a
wrapper to map input reads to pre-computed signature databases using minimap2
and/or to profile mapped reads in SAM format. (VERSION: 2.1.5 BETA)
optional arguments:
-h, --help show this help message and exit
-i [FASTQ] [[FASTQ] ...], --input [FASTQ] [[FASTQ] ...]
Input one or multiple FASTQ/FASTA file(s). Use space
to separate multiple input files.
-s [SAMFILE], --sam [SAMFILE]
Specify the input SAM file. Use '-' for standard
input.
-d [MINIMAP2_INDEX], --database [MINIMAP2_INDEX]
The path of signature database. The database can be in
FASTA format or minimap2 index (5 files).
-l [LEVEL], --dbLevel [LEVEL]
Specify the taxonomic level of the input database. You
can choose one rank from "superkingdom", "phylum",
"class", "order", "family", "genus", "species" and
"strain". The value will be auto-detected if the input
database ended with levels (e.g. GOTTCHA_db.species).
-ti [FILE], --taxInfo [FILE]
Specify the path of taxonomy information file
(taxonomy.tsv). GOTTCHA2 will try to locate this file
when user doesn't specify a path. If '--database'
option is used, the program will try to find this file
in the directory of specified database. If not, the
'database' directory under the location of gottcha.py
will be used as default.
-np, --nanopore Adjust options for Nanopore reads. The 'mismatch'
option will be ignored. [-xm map-ont -mr 1]
-pm <INT>, --mismatch <INT>
Mismatch penalty for the aligner. [default: 10]
-e [TAXID], --extract [TAXID]
Extract reads mapping to a specific TAXID. [default:
None]
-fm [STR], --format [STR]
Format of the results; available options include tsv,
csv or biom. [default: tsv]
-r [FIELD], --relAbu [FIELD]
The field will be used to calculate relative
abundance. You can specify one of the following
fields: "LINEAR_LENGTH", "TOTAL_BP_MAPPED",
"READ_COUNT" and "LINEAR_DOC". [default: ROLLUP_DOC]
-t <INT>, --threads <INT>
Number of threads [default: 1]
-o [DIR], --outdir [DIR]
Output directory [default: .]
-p <STR>, --prefix <STR>
Prefix of the output file [default:
<INPUT_FILE_PREFIX>]
-xm <STR>, --presetx <STR>
The preset option (-x) for minimap2. Default value
'sr' for short reads. [default: sr]
-mc <FLOAT>, --minCov <FLOAT>
Minimum linear coverage to be considered valid in
abundance calculation [default: 0.005]
-mr <INT>, --minReads <INT>
Minimum number of reads to be considered valid in
abundance calculation [default: 3]
-ml <INT>, --minLen <INT>
Minimum unique length to be considered valid in
abundance calculation [default: 60]
-mz <FLOAT>, --maxZscore <FLOAT>
Maximum estimated zscore of depths of mapped region
[default: 10]
-nc, --noCutoff Remove all cutoffs. This option is equivalent to use
[-mc 0 -mr 0 -ml 0].
-c, --stdout Write on standard output.
-v, --version Print version number.
--silent Disable all messages.
--debug Debug mode. Provide verbose running messages and keep
all temporary files.
```
```
usage: pull_database.py [-h] [-u URL] [-r RANK]
This script will pull the latest version of the Gottcha2 database.
optional arguments:
-h, --help show this help message and exit
-u URL, --url URL specify a URL to pull from (will override the default)
-r RANK, --rank RANK taxonomic rank of the database (superkingdom, phylum, class, order, famiily, genus, species)
```
Raw data
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"description": "[](https://gottcha2.readthedocs.io/en/latest/_images/gottcha_icon.png)\n\n# Genomic Origin Through Taxonomic CHAllenge (GOTTCHA)\n\n[](https://github.com/poeli/GOTTCHA2/actions?query=workflow%3Agottcha)\n\n\nGOTTCHA is an application of a novel, gene-independent and signature-based metagenomic taxonomic profiling\nmethod with significantly smaller false discovery rates (FDR) that is laptop deployable. Our algorithm was\ntested and validated on twenty synthetic and mock datasets ranging in community composition and complexity,\nwas applied successfully to data generated from spiked environmental and clinical samples, and robustly\ndemonstrates superior performance compared with other available tools.\n\nGOTTCHAv2 is currently under development in BETA stage. Pre-built databases for v1 are incompatible with v2.\n\n-------------------------------------------------------------------\n## DEPENDENCIES\n\nGOTTCHA2 profiler is written in Python3 and leverage minimap2 to map reads to signature sequences. In order to run GOTTCHA2 correctly, your system requires to have following dependencies installed correctly. The YAML file for Conda environment can be found in `environment.yml`.\n\n- Python 3.4+\n- minimap2 2.1+\n- pandas\n- samtools\n\n-------------------------------------------------------------------\n## QUICK START\n\n1. Download or git clone GOTTCHA2 from this repository and `cd` to the cloned directory.\n\n2. Run `pip install .`\n\n2. Download the latest version of the GOTTCHA2 database. (This step may take some time)\n\n https://ref-db.edgebioinformatics.org/gottcha2/RefSeq-r220/\n\n3. Run GOTTCHA2:\n \n $ gottcha2.py -d RefSeq-r220_BAVxH-cg/gottcha_db.species.fna -t 8 -i <FASTQ>\n \n OR\n \n $ gottcha2 profile -d RefSeq-r220_BAVxH-cg/gottcha_db.species.fna -t 8 -i <FASTQ>\n\n-------------------------------------------------------------------\n## RESULT\n\nGOTTCHA2 can output the profiling results in either CSV, TSV or BIOM format.\n- summary (.tsv or .csv) - A summary of profiling results (10 columns) in taxonomic ranks breakdown\n- full (.tsv or .csv) - A full profiling results including unfiltered profiling results and additional columns\n- lineage (.lineage.tsv or .lineage.tsv) - output lineage and abundance of the profiled taxon per line\n- extract (.extract[TAXID].fastq) - Extracted reads for a specific taxon.\n\n#### Summary and full reports\n\nA full GOTTCHA2 report has 22 columns in tab-delimited format. The summary report is a brief version that has the first 10 columns and qualified taxonomies. The report lists profiling results at taxonomic rank breakdown from superkingdom to strain, following by other information listed below. The rollup depth of coverage (ROLLUP_DOC) is used to calculate relative abundance (column 10) by default, as well as other relative abundance calculations (column 19-21).\n\n| COLUMN | NAME | DESCRIPTION | NOTE |\n|--------|-----------------------|----------------------------------------------------------------------------|------------------------------------------------------------|\n| 1 | LEVEL | Taxonomic rank | |\n| 2 | NAME | Taxonomic name | |\n| 3 | TAXID | Taxonomic ID | |\n| 4 | READ_COUNT | Number of mapped reads | |\n| 5 | TOTAL_BP_MAPPED | Total bases of mapped reads | |\n| 6 | TOTAL_BP_MISMATCH | Total mismatch bases of mapped reads | |\n| 7 | LINEAR_LENGTH | Number of non-overlapping bases covering the signatures | |\n| 8 | LINEAR_DOC | Linear depth-of-coverage | = TOTAL_BP_MAPPED / LINEAR_LENGTH |\n| 9 | ROLLUP_DOC | Rollup depth-of-coverage | = \u2211 DOC of sub-level |\n| 10 | REL_ABUNDANCE | Relative abundance (normalized abundance) | = ABUNDANCE / \u2211 ABUNDANCE of given level |\n| 11 | LINEAR_COV | Proportion of covered signatures to total signatures of mapped organism(s) | = LINEAR_LENGTH / SIG_LENGTH_TOL |\n| 12 | LINEAR_COV_MAPPED_SIG | Proportion of covered signatures to mapped signatures | = LINEAR_LENGTH / SIG_LENGTH_MAPPED |\n| 13 | BEST_LINEAR_COV | Best linear coverage of corresponding taxons | |\n| 14 | DOC | Average depth-of-coverage | = TOTAL_BP_MAPPED / SIG_LENGTH_TOL |\n| 15 | BEST_DOC | Best DOC of corresponding taxons | |\n| 16 | SIG_LENGTH_TOL | Length of all signatures in mapped organism(s) | |\n| 17 | SIG_LENGTH_MAPPED | Length of signatures in mapped signature fragment(s) | |\n| 18 | ABUNDANCE | abundance of the taxon | value of either ROLLUP_DOC, READ_COUNT or TOTAL_BP_MAPPED |\n| 19 | ZSCORE | Estimated Z-score of depth of coverage of the mapped region | |\n| 20 | NOTE | Only note the reason for being filtered out | |\n\n-------------------------------------------------------------------\n## USAGE\n\n```\nusage: gottcha2.py [-h] [-i [FASTQ] [[FASTQ] ...]] [-s [SAMFILE]]\n [-d [MINIMAP2_INDEX]] [-l [LEVEL]] [-ti [FILE]] [-np]\n [-pm <INT>] [-e [TAXID]] [-fm [STR]] [-r [FIELD]]\n [-t <INT>] [-o [DIR]] [-p <STR>] [-xm <STR>] [-mc <FLOAT>]\n [-mr <INT>] [-ml <INT>] [-mz <FLOAT>] [-nc] [-c] [-v]\n [--silent] [--debug]\n\nGenomic Origin Through Taxonomic CHAllenge (GOTTCHA) is an annotation-\nindependent and signature-based metagenomic taxonomic profiling tool that has\nsignificantly smaller FDR than other profiling tools. This program is a\nwrapper to map input reads to pre-computed signature databases using minimap2\nand/or to profile mapped reads in SAM format. (VERSION: 2.1.5 BETA)\n\noptional arguments:\n -h, --help show this help message and exit\n -i [FASTQ] [[FASTQ] ...], --input [FASTQ] [[FASTQ] ...]\n Input one or multiple FASTQ/FASTA file(s). Use space\n to separate multiple input files.\n -s [SAMFILE], --sam [SAMFILE]\n Specify the input SAM file. Use '-' for standard\n input.\n -d [MINIMAP2_INDEX], --database [MINIMAP2_INDEX]\n The path of signature database. The database can be in\n FASTA format or minimap2 index (5 files).\n -l [LEVEL], --dbLevel [LEVEL]\n Specify the taxonomic level of the input database. You\n can choose one rank from \"superkingdom\", \"phylum\",\n \"class\", \"order\", \"family\", \"genus\", \"species\" and\n \"strain\". The value will be auto-detected if the input\n database ended with levels (e.g. GOTTCHA_db.species).\n -ti [FILE], --taxInfo [FILE]\n Specify the path of taxonomy information file\n (taxonomy.tsv). GOTTCHA2 will try to locate this file\n when user doesn't specify a path. If '--database'\n option is used, the program will try to find this file\n in the directory of specified database. If not, the\n 'database' directory under the location of gottcha.py\n will be used as default.\n -np, --nanopore Adjust options for Nanopore reads. The 'mismatch'\n option will be ignored. [-xm map-ont -mr 1]\n -pm <INT>, --mismatch <INT>\n Mismatch penalty for the aligner. [default: 10]\n -e [TAXID], --extract [TAXID]\n Extract reads mapping to a specific TAXID. [default:\n None]\n -fm [STR], --format [STR]\n Format of the results; available options include tsv,\n csv or biom. [default: tsv]\n -r [FIELD], --relAbu [FIELD]\n The field will be used to calculate relative\n abundance. You can specify one of the following\n fields: \"LINEAR_LENGTH\", \"TOTAL_BP_MAPPED\",\n \"READ_COUNT\" and \"LINEAR_DOC\". [default: ROLLUP_DOC]\n -t <INT>, --threads <INT>\n Number of threads [default: 1]\n -o [DIR], --outdir [DIR]\n Output directory [default: .]\n -p <STR>, --prefix <STR>\n Prefix of the output file [default:\n <INPUT_FILE_PREFIX>]\n -xm <STR>, --presetx <STR>\n The preset option (-x) for minimap2. Default value\n 'sr' for short reads. [default: sr]\n -mc <FLOAT>, --minCov <FLOAT>\n Minimum linear coverage to be considered valid in\n abundance calculation [default: 0.005]\n -mr <INT>, --minReads <INT>\n Minimum number of reads to be considered valid in\n abundance calculation [default: 3]\n -ml <INT>, --minLen <INT>\n Minimum unique length to be considered valid in\n abundance calculation [default: 60]\n -mz <FLOAT>, --maxZscore <FLOAT>\n Maximum estimated zscore of depths of mapped region\n [default: 10]\n -nc, --noCutoff Remove all cutoffs. This option is equivalent to use\n [-mc 0 -mr 0 -ml 0].\n -c, --stdout Write on standard output.\n -v, --version Print version number.\n --silent Disable all messages.\n --debug Debug mode. Provide verbose running messages and keep\n all temporary files.\n```\n```\nusage: pull_database.py [-h] [-u URL] [-r RANK]\n\nThis script will pull the latest version of the Gottcha2 database.\n\noptional arguments:\n -h, --help show this help message and exit\n -u URL, --url URL specify a URL to pull from (will override the default)\n -r RANK, --rank RANK taxonomic rank of the database (superkingdom, phylum, class, order, famiily, genus, species)\n```\n",
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