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Machine-learning model for the prioritization of CNVs with uncertainty estimates in rare disease patients

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CNVscore: A framework for the prioritization of CNVs with uncertainty estimates in rare disease patients


Welcome to the official Github repository of CNVscore.

The CNVscore manuscript is available on:

Requena, Francisco, et al. "CNVscore calculates pathogenicity scores for copy number variants together with uncertainty estimates accounting for learning biases in reference Mendelian disorder datasets." medRxiv (2022). https://doi.org/10.1101/2022.06.23.22276396

Table of contents

Overview

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API visual documentation

You can test the API directly on your web browser: API UI

API query example

curl -X POST "http://35.180.225.167:3838/classifier?input_chrom=17&input_start=61158866&input_end=61353248&input_type=deletion"

Response example

[
  {
    "chrom": "17",
    "start": "61,158,866",
    "end": "61,353,248",
    "variant_class": "deletion",
    "cnvscore": 0.9132,
    "uncertainty_level": 1,
    "rules": "min_expression<=39 & max_cadd>34.5 (risk:0.87 - support:3910);min_expression<=33.5 & max_cadd>37.5 (risk:0.88 - support:3445);loeuf>0.8085 & cpg_density>1.5 (risk:0.81 - support:789);enhancer<=0.000282170504594472 & max_cadd>40.5 (risk:0.87 - support:3544);pli>82.5 & max_cadd>25.7 (risk:0.91 - support:1385)"
  }
]

Availability

CNVscore can be deployed as a private API service through a Docker image without external dependencies. Instructions to locally deploy the API service are provided in the next section.

In addition, CNVscore can be queried and interrogated at http://cnvxplorer.com.

Docker installation

# Note: the first session after the deployment is slower since the application loads all the data required

git clone https://github.com/RausellLab/CNVscore.git

cd CNVscore 

docker build -t cnvscore . -f api/Dockerfile . # The tag "cnvscore" is optional

docker run -d -p 3838:3838 cnvscore # -p (specify port) -d (detached mode)

# The port 3838 is optional. Please make sure you set a port not blocked by firewalls.
# If you change the port number (3838) by any other, make sure to set it in the Dockerfile (EXPOSE instruction)

Authors and contact

CNVscore has been developed by Francisco Requena and Antonio Rausell, at the Clinical Bioinformatics Laboratory of the Imagine Institute in Paris, France.

Please address comments and questions about CNVscore to: * Francisco Requena - francisco.requena@institutimagine.org * Antonio Rausell - antonio.rausell@institutimagine.org

License

This project is licensed under the GNU General Public License 3 - see the LICENSE file for details

See the License for the specific language governing permissions and limitations under the License.

Copyright 2021 Clinical BioInformatics Laboratory - Institut Imagine

Disclaimer

CNVscore or any document available from this server are distributed on an “AS IS” BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express, implied, or statutory, including, but not limited to, any implied warranties of merchantability, fitness for a particular purpose and freedom from infringement, or that CNVscore or any documents available from this server will be error-free.

In no event will the Imagine Institute, the Clinical Bioinformatics lab, or any of its members be liable for any damages, including but not limited to direct, indirect, special, or consequential damages, arising out of, resulting from, or in any way connected with the use of CNVscore or documents available from it.

Reference

TBA

News

You may follow us in Twitter for regular news and updates: https://twitter.com/AntonioRausell

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Machine-learning model for the prioritization of CNVs with uncertainty estimates in rare disease patients

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