2.2.1

• Added exomiser example
• Recode iderare_phenotyping script using iderare-pheno Python library
  Full Changelog: 2.1.1...2.2.1

2.1.1

What's new :

• Updating clinical_data.txt , clinical_data_example.txt , and README.md with correct impending liver failure SNOMEDCT code

Full Changelog: 2.1.0...2.1.1

2.1.0

Changelog :

• Synchronized iderare_pheno.py interactive implementation on Streamlit
• Handling exception and limit top-100 data to be analyzed by stats.linkage for iderare_pheno.threshold_similarity function
• Fixed template_iderare.yml to be fully blank

Full Changelog: 2.0.1...2.1.0

2.0

Summary

• Expanding IDeRare pipeline encompassing translational bioinformatics from clinical EMR data to HPO
• Added following database subset Phenotype Data Source :
  1. ICD10 to OMIM
  2. LOINC to HPO
  3. OMIM to HPO
  4. ORPHA to HPO
  5. ORPHA to OMIM
  6. SNOMED to HPO
  7. SNOMED to ORPHA

Features :

• Convert the phenotype data to HPO code (accept mixed SNOMED, LOINC, and HPO code)
• Linkage analysis of differential diagnosis (accept mixed SNOMED, ICD10, ORPHA, OMIM code)
• Similarity scoring of differential diagnosis
• Gene-disease recommendation based on the phenotype data.
• Similarity scoring of recommended causative gene and disease.
• Linkage analysis of recommended causative gene and disease based on phenotype data.
• Example of the clinical data provided at Clinical Information Example section

1.0

IDeRare

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

Note: currently IDeRare paper is being considered journal submission.

Description

• This pipeline is designed to be used in Linux environment
• Original paper may used different version of tools, and the prerequisite used in this pipeline is the latest version of the tools
• This pipeline is designed and tested with Indonesia rare disease trio patient, but it should be also usable for general cases of rare disease variant discovery from Exome Sequences data given paired end .fq.gz file and HPO data(s)
• Ensure you have at least 250GB free for database and application setup, and 100GB free for each Trio family exome set
• The .yaml file path are assuming all the folder are stored in Downloads folder with subfolder of Database (for RefSeq, dbNSFP, dbSNP, ClinVar), Sandbox (for application and its database), IDeRare (git cloned folder)