| Name | MetaPont JSON |
| Version |
0.0.3
JSON |
| download |
| home_page | https://github.com/TheHuwsLab/MetaPont |
| Summary | MetaPont - A tool to bridge the gap between the output of metagenomic tools and the analysis of the data |
| upload_time | 2024-11-28 20:39:21 |
| maintainer | None |
| docs_url | None |
| author | Nicholas Dimonaco |
| requires_python | >=3.6 |
| license | None |
| keywords |
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
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| coveralls test coverage |
No coveralls.
|
# MetaPont
**MetaPont** - A tool to bridge the gap between the output of metagenomic tools and the analysis of the data
## Features - These are the current aims of this project - Still under development
- **Targeted Functional Analysis:** Search for specific functional IDs (e.g., GO terms) within the `_Final_Contig.tsv` files provided by the HuwsLab Metagenome Workflow (https://github.com/TheHuwsLab/Metagenome_Workflow) .
- **Taxonomic Breakdown:** Extract genus-level taxonomy information and calculate their proportions in the dataset.
- **Batch Processing:** Analyse all `_Final_Contig.tsv` files in a specified directory.
- **Customisable Output:** Save results in a format suitable for downstream analysis.
---
## Installation
### Prerequisites
Ensure you have the following installed:
- Python ~3.6 or later
### Installation via pip
MetaPont is provided as a pip distribution.
```bash
pip install MetaPont
```
---
## Usage
---
### Extract-By-Function Command-line Arguments
```Extract-By-Function -h ```
```bash
usage: Extract_By_Function.py [-h] -d DIRECTORY -f FUNCTION_ID -o OUTPUT
[-m MIN_PROPORTION] [-top TOP_TAXA]
MetaPont v0.0.3: Extract-By-Function - Identify taxa contributing to a
specific function.
options:
-h, --help show this help message and exit
-d DIRECTORY, --directory DIRECTORY
Directory containing TSV files to analyse.
-f FUNCTION_ID, --function_id FUNCTION_ID
Specific function ID to search for (e.g.,
'GO:0016597').
-o OUTPUT, --output OUTPUT
Output file to save results.
-m MIN_PROPORTION, --min_proportion MIN_PROPORTION
Minimum proportion threshold for taxa to be included
in the output.
-top TOP_TAXA, --top_taxa TOP_TAXA
Top n taxa to be included in the output.
```
The `Extract-By-Function` tool provides several command-line options: \
Note: Either -m or -top is required.
| Option | Description | Required | Default |
|--------------------------|------------------------------------------------------------|----------|---------|
| `-d`, `--directory` | Directory containing `_Final_Contig.tsv` files to analyse. | Yes | None |
| `-f`, `--function_id` | Functional ID to search for (e.g., `GO:0016597`). | Yes | None |
| `-m`, `--min_proportion` | Minimum proportion needed for reporting. | Yes/No | None |
| `-top`, `--top_taxa` | Number of taxa to report. | Yes/No | None |
| `-o`, `--output` | Output file name to save results. | Yes | None |
### Example
To search for the functional ID `GO:0016597` in all `_Final_Contig.tsv` files within the `test_data/` directory:
```bash
Extract=By-Function -d .../test_data/Final_contig/ -f GO:0016597 -top 3 -o .../test_data/Final_Contig/Extract_By_Function_Out/results.tsv
```
---
## Output
The tool generates a tab-delimited output file with the following columns:
1. **Sample:** Name of the processed Sample.
2. **Taxa:** Genus-level taxonomic assignment extracted from the `Lineage` column.
3. **Reads Assigned (Function):** Number of reads assigned to contigs with the given functional ID.
3. **Proportion:** Proportion of reads assigned to contigs of stated Taxa with the given functional ID within the sample.
4. **Proportion (Total Reads):** Proportion of reads assigned to contigs of stated Taxa with the given functional ID within the total reads of the sample.
Example output:
```
Function ID: GO:0016597
Sample Taxa Reads Assigned (Function) Proportion (Function) Proportion (Total Reads)
PN0536_0001_S1_Final_Contig.tsv Lactobacillus 111963 0.602 0.004
PN0536_0003_S83_Final_Contig.tsv Lactobacillus 20072 0.457 0.001
PN0536_0002_S2_Final_Contig.tsv Acutalibacter 145222 0.795 0.005
PN0536_0004_S3_Final_Contig.tsv Lactobacillus 40076 0.404 0.002
```
---
### Workflow - unfinished
1. The script reads `_Final_Contig.tsv` files from the specified directory.
2. For each file, it searches for occurrences of the given functional ID within specific columns.
3. Matches are associated with genus-level taxonomic information extracted from the `Lineage` column.
4. Taxa proportions are calculated and saved to the output file.
---
## Extract-By-Taxa Command-line Arguments
```Extract-By-Taxa -h ```
```bash
usage: Extract_By_Taxa.py [-h] -d DIRECTORY -t TAXON -o OUTPUT -func
FUNCTIONAL_CLASSES [-top TOP_FUNCTIONS]
MetaPont: Extract Top Functions by Taxon
options:
-h, --help show this help message and exit
-d DIRECTORY, --directory DIRECTORY
Directory containing TSV files to analyse.
-t TAXON, --taxon TAXON
Target taxon to search for (e.g., 'g__Bacillus').
-o OUTPUT, --output OUTPUT
Output file to save results.
-func FUNCTIONAL_CLASSES, --functional_classes FUNCTIONAL_CLASSES
Which functional classes to report (e.g. GO,EC,KEGG
etc).
-top TOP_FUNCTIONS, --top_functions TOP_FUNCTIONS
Top n functions to include in the output for each
sample (default: 3).
```
The `Extract-By-Taxa` tool provides several command-line options:
| Option | Description | Required | Default |
|-----------------------------------|-------------------------------------------------------------|----------|---------|
| `-d`, `--directory` | Directory containing `_Fincal_Contig.tsv` files to analyse. | Yes | None |
| `-t`, `--taxon` | Taxa to search for (e.g., `g__Bacillus`). | Yes | None |
| `-func`, `--functional_classes` | Functional classes to report (e.g. GO,EC,KEGG etc). | Yes | None |
| `-top`, `--top_taxa` | Number of functions to report (default 3). | No | None |
| `-o`, `--output` | Output file name to save results. | Yes | None |
### Example
To search for the top reported functions for taxon `g__Bacillus` in all `_Final_Contig.tsv` files within the `test_data/` directory:
```bash
Extract-By-Taxa -d .../test_data/Final_Contig -t g__Bacillus -o .../test_data/Final_Contig/Extract_By_Taxa/results.tsv -func GO
```
---
## Output
The tool generates a tab-delimited output file with the following columns:
1. **Sample:** Name of the processed Sample.
2. **Function:** Reported 'top' function.
3. **Num of Assignments (Functions):** Number of times the function has been assigned across all contigs reported as chosen Taxon.
Example output:
```
Selected Taxon: g__Bacillus
Sample Function Num of Assignments
PN0536_0001_S1 GO:0008150 296
PN0536_0001_S1 GO:0003674 285
PN0536_0001_S1 GO:0005575 254
PN0536_0003_S83 GO:0005575 45
PN0536_0003_S83 GO:0008150 44
PN0536_0003_S83 GO:0003674 43
PN0536_0002_S2 GO:0005575 5
PN0536_0002_S2 GO:0008150 5
PN0536_0002_S2 GO:0005623 4
PN0536_0004_S3 GO:0008150 4
PN0536_0004_S3 GO:0003674 3
PN0536_0004_S3 GO:0005488 3
```
---
### Large File Handling (Might be a failure point)
The script uses `csv.field_size_limit` to handle exceptionally large `.tsv` files.
---
Raw data
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"description": "# MetaPont\n**MetaPont** - A tool to bridge the gap between the output of metagenomic tools and the analysis of the data\n\n## Features - These are the current aims of this project - Still under development\n\n- **Targeted Functional Analysis:** Search for specific functional IDs (e.g., GO terms) within the `_Final_Contig.tsv` files provided by the HuwsLab Metagenome Workflow (https://github.com/TheHuwsLab/Metagenome_Workflow) .\n- **Taxonomic Breakdown:** Extract genus-level taxonomy information and calculate their proportions in the dataset.\n- **Batch Processing:** Analyse all `_Final_Contig.tsv` files in a specified directory.\n- **Customisable Output:** Save results in a format suitable for downstream analysis.\n\n---\n\n## Installation\n\n### Prerequisites\n\nEnsure you have the following installed:\n\n- Python ~3.6 or later\n\n### Installation via pip\n\nMetaPont is provided as a pip distribution. \n\n```bash\npip install MetaPont \n```\n\n---\n\n## Usage\n\n--- \n### Extract-By-Function Command-line Arguments\n```Extract-By-Function -h ``` \n```bash\nusage: Extract_By_Function.py [-h] -d DIRECTORY -f FUNCTION_ID -o OUTPUT\n [-m MIN_PROPORTION] [-top TOP_TAXA]\n\nMetaPont v0.0.3: Extract-By-Function - Identify taxa contributing to a\nspecific function.\n\noptions:\n -h, --help show this help message and exit\n -d DIRECTORY, --directory DIRECTORY\n Directory containing TSV files to analyse.\n -f FUNCTION_ID, --function_id FUNCTION_ID\n Specific function ID to search for (e.g.,\n 'GO:0016597').\n -o OUTPUT, --output OUTPUT\n Output file to save results.\n -m MIN_PROPORTION, --min_proportion MIN_PROPORTION\n Minimum proportion threshold for taxa to be included\n in the output.\n -top TOP_TAXA, --top_taxa TOP_TAXA\n Top n taxa to be included in the output.\n\n```\n\nThe `Extract-By-Function` tool provides several command-line options: \\\nNote: Either -m or -top is required.\n\n| Option | Description | Required | Default |\n|--------------------------|------------------------------------------------------------|----------|---------|\n| `-d`, `--directory` | Directory containing `_Final_Contig.tsv` files to analyse. | Yes | None |\n| `-f`, `--function_id` | Functional ID to search for (e.g., `GO:0016597`). | Yes | None |\n| `-m`, `--min_proportion` | Minimum proportion needed for reporting. | Yes/No | None |\n| `-top`, `--top_taxa` | Number of taxa to report. | Yes/No | None |\n| `-o`, `--output` | Output file name to save results. | Yes | None |\n\n### Example\n\nTo search for the functional ID `GO:0016597` in all `_Final_Contig.tsv` files within the `test_data/` directory:\n\n```bash\nExtract=By-Function -d .../test_data/Final_contig/ -f GO:0016597 -top 3 -o .../test_data/Final_Contig/Extract_By_Function_Out/results.tsv\n```\n\n---\n\n## Output\n\nThe tool generates a tab-delimited output file with the following columns:\n\n1. **Sample:** Name of the processed Sample.\n2. **Taxa:** Genus-level taxonomic assignment extracted from the `Lineage` column.\n3. **Reads Assigned (Function):** Number of reads assigned to contigs with the given functional ID.\n3. **Proportion:** Proportion of reads assigned to contigs of stated Taxa with the given functional ID within the sample.\n4. **Proportion (Total Reads):** Proportion of reads assigned to contigs of stated Taxa with the given functional ID within the total reads of the sample.\n\nExample output:\n\n```\nFunction ID: GO:0016597\nSample\tTaxa\tReads Assigned (Function)\tProportion (Function)\tProportion (Total Reads)\nPN0536_0001_S1_Final_Contig.tsv\tLactobacillus\t111963\t0.602\t0.004\nPN0536_0003_S83_Final_Contig.tsv\tLactobacillus\t20072\t0.457\t0.001\nPN0536_0002_S2_Final_Contig.tsv\tAcutalibacter\t145222\t0.795\t0.005\nPN0536_0004_S3_Final_Contig.tsv\tLactobacillus\t40076\t0.404\t0.002\n```\n\n---\n\n\n\n### Workflow - unfinished\n\n1. The script reads `_Final_Contig.tsv` files from the specified directory.\n2. For each file, it searches for occurrences of the given functional ID within specific columns.\n3. Matches are associated with genus-level taxonomic information extracted from the `Lineage` column.\n4. Taxa proportions are calculated and saved to the output file.\n\n---\n## Extract-By-Taxa Command-line Arguments\n```Extract-By-Taxa -h ``` \n```bash\nusage: Extract_By_Taxa.py [-h] -d DIRECTORY -t TAXON -o OUTPUT -func\n FUNCTIONAL_CLASSES [-top TOP_FUNCTIONS]\n\nMetaPont: Extract Top Functions by Taxon\n\noptions:\n -h, --help show this help message and exit\n -d DIRECTORY, --directory DIRECTORY\n Directory containing TSV files to analyse.\n -t TAXON, --taxon TAXON\n Target taxon to search for (e.g., 'g__Bacillus').\n -o OUTPUT, --output OUTPUT\n Output file to save results.\n -func FUNCTIONAL_CLASSES, --functional_classes FUNCTIONAL_CLASSES\n Which functional classes to report (e.g. GO,EC,KEGG\n etc).\n -top TOP_FUNCTIONS, --top_functions TOP_FUNCTIONS\n Top n functions to include in the output for each\n sample (default: 3).\n\n```\n\nThe `Extract-By-Taxa` tool provides several command-line options: \n\n\n| Option | Description | Required | Default |\n|-----------------------------------|-------------------------------------------------------------|----------|---------|\n| `-d`, `--directory` | Directory containing `_Fincal_Contig.tsv` files to analyse. | Yes | None |\n| `-t`, `--taxon` | Taxa to search for (e.g., `g__Bacillus`). | Yes | None |\n| `-func`, `--functional_classes` | Functional classes to report (e.g. GO,EC,KEGG etc). | Yes | None |\n| `-top`, `--top_taxa` | Number of functions to report (default 3). | No | None |\n| `-o`, `--output` | Output file name to save results. | Yes | None |\n\n### Example\n\nTo search for the top reported functions for taxon `g__Bacillus` in all `_Final_Contig.tsv` files within the `test_data/` directory:\n\n```bash\nExtract-By-Taxa -d .../test_data/Final_Contig -t g__Bacillus -o .../test_data/Final_Contig/Extract_By_Taxa/results.tsv -func GO\n```\n\n---\n## Output\n\nThe tool generates a tab-delimited output file with the following columns:\n\n1. **Sample:** Name of the processed Sample.\n2. **Function:** Reported 'top' function.\n3. **Num of Assignments (Functions):** Number of times the function has been assigned across all contigs reported as chosen Taxon.\n\nExample output:\n\n```\nSelected Taxon: g__Bacillus\nSample\tFunction\tNum of Assignments\nPN0536_0001_S1\tGO:0008150\t296\nPN0536_0001_S1\tGO:0003674\t285\nPN0536_0001_S1\tGO:0005575\t254\nPN0536_0003_S83\tGO:0005575\t45\nPN0536_0003_S83\tGO:0008150\t44\nPN0536_0003_S83\tGO:0003674\t43\nPN0536_0002_S2\tGO:0005575\t5\nPN0536_0002_S2\tGO:0008150\t5\nPN0536_0002_S2\tGO:0005623\t4\nPN0536_0004_S3\tGO:0008150\t4\nPN0536_0004_S3\tGO:0003674\t3\nPN0536_0004_S3\tGO:0005488\t3\n\n```\n\n---\n\n### Large File Handling (Might be a failure point)\n\nThe script uses `csv.field_size_limit` to handle exceptionally large `.tsv` files.\n\n---\n\n\n",
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