Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

Awesome Lists | Featured Topics | Projects

https://github.com/ivanwilliammd/iderare-pheno

IdeRare Phenotype Analysis suite : Convert Indonesia SATUSEHAT terminology (SNOMED-CT, LOINC, ICD-10) to Rare Disease Terminology / Ontology (HPO, OMIM) and find the likelihood differential gene and disease explaining patient phenotype
https://github.com/ivanwilliammd/iderare-pheno

phenotype phenotype-exchange-format phenotype-genotype-information phenotype-ontologies phenotype-prediction rare-disease

Last synced: about 1 month ago
JSON representation

IdeRare Phenotype Analysis suite : Convert Indonesia SATUSEHAT terminology (SNOMED-CT, LOINC, ICD-10) to Rare Disease Terminology / Ontology (HPO, OMIM) and find the likelihood differential gene and disease explaining patient phenotype

Awesome Lists containing this project

README 

        
# [IDeRare-Pheno](https://pypi.org/project/iderare_pheno/)





    

        CI

    

    

        PyPI

    



    

        License

    

    

        Streamlit

    





IDeRare or "Indonesia Exome Rare Disease Variant Discovery Pipeline" is a simple and ready to use variant discovery pipeline to discover rare disease variants from exome sequencing data. 



This repository is **the first part** of IDeRare workflow for **phenotype analysis**. For complete pipeline for _**phenotype-genotype analysis**_, kindly refer to [IDeRare Github repository](https://github.com/ivanwilliammd/IDeRare).



## Authored by 

Ivan William Harsonoa, Yulia Arianib, Beben Benyaminc,d,e, Fadilah Fadilahf,g, Dwi Ari Pujiantob, Cut Nurul Hafifahh



aDoctoral Program in Biomedical Sciences, Faculty of Medicine, Universitas Indonesia, Jakarta, Indonesia.
 

bDepartment of Medical Biology, Faculty of Medicine, Universitas Indonesia, Jakarta, Indonesia.
 

cAustralian Centre for Precision Health, University of South Australia, Adelaide, SA, 5000, Australia. 


dUniSA Allied Health and Human Performance, University of South Australia, Adelaide, SA, 5000, Australia. 


eSouth Australian Health and Medical Research Institute (SAHMRI), University of South Australia, Adelaide, SA, 5000, Australia. 


fDepartment of Medical Chemistry, Faculty of Medicine, Universitas Indonesia, Jalan Salemba Raya number 4, Jakarta, 10430, Indonesia.


gBioinformatics Core Facilities - IMERI, Faculty of Medicine, Universitas Indonesia, Jalan Salemba Raya number 6, Jakarta, 10430, Indonesia .


hDepartment of Child Health, Dr. Cipto Mangunkusumo Hospital, Faculty of Medicine, University of Indonesia, Jakarta, Indonesia. 



## How to Cite

Please kindly cite the main paper titled *"IDeRare: a lightweight and extensible open-source phenotype and exome analysis pipeline for germline rare disease diagnosis"* available at [https://doi.org/10.1093/jamiaopen/ooae052](https://doi.org/10.1093/jamiaopen/ooae052)



**Example :**

```

Ivan William Harsono, Yulia Ariani, Beben Benyamin, Fadilah Fadilah, Dwi Ari Pujianto, Cut Nurul Hafifah, IDeRare: a lightweight and extensible open-source phenotype and exome analysis pipeline for germline rare disease diagnosis, JAMIA Open, Volume 7, Issue 2, July 2024, ooae052, https://doi.org/10.1093/jamiaopen/ooae052

```



## Quick links

- [IDeRare full pipeline - Phenotype and Genotype](https://github.com/ivanwilliammd/IDeRare)

- [PyPI Package](https://pypi.org/project/iderare-pheno/)

- [License](https://github.com/ivanwilliammd/iderare-pheno/blob/main/LICENSE)

- [Interactive Playbook Example](https://github.com/ivanwilliammd/iderare-pheno/blob/main/Playbook.ipynb)

- Interactive Webapps Implementation of at [Streamlit](https://bioinformatics-ivanwilliamharsono.streamlitapp.com/IDeRare_Pheno)



## What does it do?



This script is recommended if you would like to do conversion, linkage analysis, similarity scoring, and gene-disease recommendation based on the phenotype data provided at [clinical_data.txt](clinical_data.txt). Full feature : 

1. Convert the phenotype data to HPO code (accept mixed SNOMED, LOINC, and HPO code)

2. Similarity scoring of differential diagnosis

3. Linkage analysis of differential diagnosis (accept mixed SNOMED, ICD-10, ORPHA, OMIM code), include dendrogram tree visualization.

    - This should help clinician to **systematically doing work-up and excluding similar diagnosis together** based on the patient\'s phenotype.

4. Gene and disease recommendation based on the phenotype data similarity scoring between **phenotype** and OMIM gene and disease databank.

5. Linkage analysis of recommended causative gene and disease based on phenotype data (include dendrogram tree visualization).

    - This should help clinician to **explore / enrich their differential diagnosis** based on the patient\'s phenotype.

6. Example of the clinical data provided at [Clinical Information Example section](#clinical-information-example)



## Installation



**iderare-pheno** requires Python 3.8 or later.



### Installing with `pip`



**iderare-pheno** is available [on PyPI](https://pypi.org/project/iderare-pheno/). Just run



```bash

pip install iderare-pheno

```



### Installing from source



To install **iderare-pheno** from source, first clone [the repository](https://github.com/ivanwilliammd/iderare-pheno):



```bash

git clone https://github.com/ivanwilliammd/iderare-pheno.git

cd iderare_pheno

```



Then run



```bash

pip install -e .

```



## Importing the library



```python

from iderare_pheno.converter import term2omim, term2orpha, term2hpo, batchconvert

from iderare_pheno.simrec import hpo2omim_similarity, omim_recommendation, hpo2name, omim2name

from iderare_pheno.utils import linkage_dendrogram, list2tsv, generate_yml

```

As the complete readthedocs.io is being finalized, please kindly refer to this [Interactive Playbook Example](https://github.com/ivanwilliammd/iderare-pheno/blob/main/Playbook.ipynb)



Note : for Streamlit implementation, use ```iderare_pheno.streamlit_utils``` instead of ```iderare_pheno.utils```, this was done to prevent file to automatically saving and showing dendrogram in Streamlit.

```python

from iderare_pheno.streamlit_utils import linkage_dendrogram, list2tsv, generate_yml

```



For Python FastAPI implementation and FHIR code extraction / parsing and deploying wsgi app, ensure you have installed the dependencies below:

```bash

pip install fastapi uvicorn a2wsgi

```



Then prepare your passenger wsgi app and main FastAPI app as below:



#### passenger_wsgi.py

```python

import os

import sys

from a2wsgi import ASGIMiddleware



# Adjust the path to your FastAPI application directory if needed

app_dir = os.path.join(os.path.dirname(__file__), 'app')

sys.path.insert(0, app_dir)



# Import your FastAPI application

from app.main import app  # Assuming your FastAPI app instance is named 'app'



# Application callable for Passenger WSGI

def application(environ, start_response):

    return ASGIMiddleware(app)(environ, start_response)

```



#### app/main.py

```python

from fastapi.responses import RedirectResponse

from iderare_pheno.fhir_parser import *



@app.get("/")

async def welcome():

    return RedirectResponse(status_code=302, url="/docs")



@app.get("/health")

async def health() -> Response :

    return {"status_code" : 200, "detail" : "The services is running, try to explore the API from Postman Collection"}



if __name__ == "__main__":

    import uvicorn

    uvicorn.run(app, host="0.0.0.0", port=8000)

```



Now you could access your http://localhost:8000 and redirected to Swagger to see the documentation of the available FastAPI endpoint. Demo example could be accessed via Postman Collection at [here](https://www.postman.com/ivanwilliamharsono/workspace/iderare-pheno/overview)



## Team



**iderare-pheno** is developed and maintained by the author(s), To learn more about who specifically contributed to this codebase, see [our contributors](https://github.com/ivanwilliammd/iderare-pheno/graphs/contributors) page.



## License



**iderare-pheno** license is derived from [IDeRare](https://github.com/ivanwilliammd/iderare)