AI-MARRVEL (AIM) is an AI system for rare genetic disease diagnosis.
It takes as input patient VCF and phenotype (formatted with HPO) to predict the causal variant(s).
In making prediction, it takes variant annotation from MARRVEL database and more,
and generates prediction score + confidence score as output.
You can use AI-MARRVEL from our website or follow the documentation to run locally.
🆕 Our paper is now published in NEJM AI!
AIM utilizes various databases for variant annotation, all of which have been compiled and are available for download. We use AWS S3 for data access, and the data can be downloaded by following these steps:
- Install the AWS CLI: Follow the instructions provided in the AWS CLI Installation Guide.
- Navigate to Your Desired Directory: Change to the directory where you want your data dependencies downloaded. For example, in Ubuntu, use:
$ cd <desired/folder/path>
- Use the following command to sync the S3 bucket to your local directory:
$ aws s3 sync s3://aim-data-dependencies-2.0-public . --no-sign-request
AIM is released as a Nextflow pipeline for easy distribution. To get it:
$ git clone -b nextflow_conversion https://github.com/LiuzLab/AI_MARRVEL
$ cd AI_MARRVEL
$ nextflow run main.nf --version
$ nextflow run main.nf --ref_dir <PATH_TO_REFERENCE_DIRECTORY>
--input_vcf <PATH_TO_INPUT_VCF_FILE>
--input_hpo <PATH_TO_INPUT_HPO_FILE>
--outdir <PATH_TO_OUTPUT_DIRECTORY>
--bed_filter <PATH_TO_BED_FILE> # Optional
--run_id [Sample Id] # Optional, default: 1
--ref_ver [Reference genome: hg19/hg38] # Optional, default: hg19
--exome_filter # Optional
Alternatively, the pipeline can be executed with a parameter file (yaml)
$ nextflow run main.nf -params-file params.yaml
NOTE: You need to create params.yaml
by copying params.yaml.example file and follow the instruction.
For more information on usage and parameters which are open for modification, please use --help
option as shown below.
$ nextflow run main.nf --help
AI-MARRVEL is licensed under GPL-3.0. You are welcomed to use it for research purpose.
For business purpose, please contact us for licensing.
- Some of the data and software included in the distribution may be subject to third-party constraints. Users of the data and software are solely responsible for establishing the nature of and complying with any such restrictions.
- AI-MARRVEL provides this data and software in good faith, but make no warranty, express or implied, nor assume any legal liability or responsibility for any purpose for which they are used.
@article{doi:10.1056/AIoa2300009,
author = {Dongxue Mao and Chaozhong Liu and Linhua Wang and Rami AI-Ouran and Cole Deisseroth and Sasidhar Pasupuleti and Seon Young Kim and Lucian Li and Jill A. Rosenfeld and Linyan Meng and Lindsay C. Burrage and Michael F. Wangler and Shinya Yamamoto and Michael Santana and Victor Perez and Priyank Shukla and Christine M. Eng and Brendan Lee and Bo Yuan and Fan Xia and Hugo J. Bellen and Pengfei Liu and Zhandong Liu },
title = {AI-MARRVEL — A Knowledge-Driven AI System for Diagnosing Mendelian Disorders},
journal = {NEJM AI},
volume = {1},
number = {5},
pages = {AIoa2300009},
year = {2024},
doi = {10.1056/AIoa2300009},
URL = {https://ai.nejm.org/doi/abs/10.1056/AIoa2300009},
eprint = {https://ai.nejm.org/doi/pdf/10.1056/AIoa2300009}
,
abstract = { AI-MARRVEL is an AI system for genetic diagnosis that improves diagnostic accuracy, surpassing state-of-the-art benchmarked methods. }
}