| Name | broad-babel JSON |
| Version |
0.1.15
JSON |
| download |
| home_page | None |
| Summary | A translator of Broad and JUMP ids to more conventional names. |
| upload_time | 2024-05-03 20:44:58 |
| maintainer | None |
| docs_url | None |
| author | Alan Munoz |
| requires_python | <4.0,>=3.9 |
| license | None |
| keywords |
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| VCS |
|
| bugtrack_url |
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| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
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| coveralls test coverage |
No coveralls.
|
# Broad_Babel
Minimal name translator of [JUMP](https://jump-cellpainting.broadinstitute.org/) consortium.
## Installation
```bash
pip install broad-babel
```
## Broad sample to standard
You can fetch a single value
```python
from broad_sample.query import sample_to_standard
broad_to_standard("BRD-K18895904-001-16-1")
# -> 'KVWDHTXUZHCGIO-UHFFFAOYSA-N'
```
If you provide multiple strings it will return dictionary.
```python
broad_to_standard(("BRD-K36461289-001-05-8", "ccsbBroad304_16164"))
# {'BRD-K36461289-001-05-8': 'SCIMP', 'ccsbBroad304_16164': 'PIMZUZSSNYHVCU-KBLUICEQSA-N'}
```
## Export database as csv
```python
from broad_sample.query import export_csv
export_csv("./output.csv")
```
## Custom querying
The available fields are:
- perturbation: Dataset of origin for a given entry
- JCP2022: Identifier from the JUMP dataset
- standard_key: Gene Entrez id for gene-related perturbations, and InChIKey for compound perturbations
- broad_sample: Internal Broad ID
- pert_type: Type of perturbation, options are trt (treatment), control, negcon (Negative Control), poscon_cp (Positive Control, Compound Probe), poscon_diverse, poscon_orf, and poscon (Positive Control).
- NCBI_Gene_ID: NCBI identifier, only applicable to ORF and CRISPR
You can fetch any field using another (note that the output is a list of tuples)
```python
run_query(query="JCP2022_915119", input_column="JCP2022", output_column="broad_sample")
# [('ccsbBroad304_16164',)]
```
Note that there are some duplicates that arise from both between orf and crispr perturbations, but also within orf standard_keys.
```python
run_query("ccsbBroad304_00900", input_column = "broad_sample", output_column = "*")
# [('crispr', 'JCP2022_803621', 'KCNN1', 'ccsbBroad304_00900', 'trt', None),
# ('orf', 'JCP2022_900842', 'KCNN1', 'ccsbBroad304_00900', 'trt', None),
# ('Target1_orf', None, 'KCNN1', 'ccsbBroad304_00900', 'trt', None)]
```
It is also possible to use fuzzy querying by changing the operator argument and adding "%" to out key.
```python
run_query(
"BRD-K21728777%",
input_column="broad_sample",
output_column="*",
operator="LIKE",
)
# [('compound',
# 'JCP2022_037716',
# 'IVUGFMLRJOCGAS-UHFFFAOYSA-N',
# 'BRD-K21728777-001-02-3',
# 'control',
# 'poscon_cp'),
# ('Target2_compound',
# None,
# 'IVUGFMLRJOCGAS-UHFFFAOYSA-N',
# 'BRD-K21728777-001-02-3',
# 'control',
# 'poscon_cp')]
```
## Additional documentation
Metadata sources and additional documentation is available [here](./docs).
Raw data
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"description": "# Broad_Babel\n\nMinimal name translator of [JUMP](https://jump-cellpainting.broadinstitute.org/) consortium.\n\n## Installation\n\n```bash\npip install broad-babel\n```\n\n## Broad sample to standard \nYou can fetch a single value\n```python\nfrom broad_sample.query import sample_to_standard\n\nbroad_to_standard(\"BRD-K18895904-001-16-1\") \n# -> 'KVWDHTXUZHCGIO-UHFFFAOYSA-N'\n```\nIf you provide multiple strings it will return dictionary.\n\n```python\nbroad_to_standard((\"BRD-K36461289-001-05-8\", \"ccsbBroad304_16164\")) \n# {'BRD-K36461289-001-05-8': 'SCIMP', 'ccsbBroad304_16164': 'PIMZUZSSNYHVCU-KBLUICEQSA-N'}\n```\n\n## Export database as csv\n```python\nfrom broad_sample.query import export_csv\n\nexport_csv(\"./output.csv\")\n```\n\n## Custom querying\nThe available fields are:\n- perturbation: Dataset of origin for a given entry\n- JCP2022: Identifier from the JUMP dataset\n- standard_key: Gene Entrez id for gene-related perturbations, and InChIKey for compound perturbations\n- broad_sample: Internal Broad ID\n- pert_type: Type of perturbation, options are trt (treatment), control, negcon (Negative Control), poscon_cp (Positive Control, Compound Probe), poscon_diverse, poscon_orf, and poscon (Positive Control).\n- NCBI_Gene_ID: NCBI identifier, only applicable to ORF and CRISPR\n\nYou can fetch any field using another (note that the output is a list of tuples)\n\n```python\nrun_query(query=\"JCP2022_915119\", input_column=\"JCP2022\", output_column=\"broad_sample\")\n# [('ccsbBroad304_16164',)]\n```\n\nNote that there are some duplicates that arise from both between orf and crispr perturbations, but also within orf standard_keys.\n\n```python\nrun_query(\"ccsbBroad304_00900\", input_column = \"broad_sample\", output_column = \"*\")\n\n# [('crispr', 'JCP2022_803621', 'KCNN1', 'ccsbBroad304_00900', 'trt', None),\n# ('orf', 'JCP2022_900842', 'KCNN1', 'ccsbBroad304_00900', 'trt', None),\n# ('Target1_orf', None, 'KCNN1', 'ccsbBroad304_00900', 'trt', None)]\n```\n\nIt is also possible to use fuzzy querying by changing the operator argument and adding \"%\" to out key.\n\n```python\n run_query(\n \"BRD-K21728777%\",\n input_column=\"broad_sample\",\n output_column=\"*\",\n operator=\"LIKE\",\n )\n\n# [('compound',\n# 'JCP2022_037716',\n# 'IVUGFMLRJOCGAS-UHFFFAOYSA-N',\n# 'BRD-K21728777-001-02-3',\n# 'control',\n# 'poscon_cp'),\n# ('Target2_compound',\n# None,\n# 'IVUGFMLRJOCGAS-UHFFFAOYSA-N',\n# 'BRD-K21728777-001-02-3',\n# 'control',\n# 'poscon_cp')]\n```\n\n## Additional documentation\nMetadata sources and additional documentation is available [here](./docs). \n",
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