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Retrieval of the disease association and evidence from the Open Targets Platform, annotation of the association evidence through Clinvar, Sequence Ontology and PanelApp APIs, and finally filter and prioritise the protective targets when they possess LoF.

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ProGoF

ProGoF is Python-based script collection that can be run to analyse target-disease association data from Open Targets Platform and to annotate them through ClinVar, PanelApp and Sequence Ontology databases for interested list of genes.

Requirements

  • Python : 3.8
    • pandas : 1.1.3
    • argparse : 1.1
    • requests : 2.24.0
    • xml-python : 0.4.3

Run

The scripts can be run with the following inputs:

source : This is the source for which the retrieval will be done. It can be ClinVar somatic and germline (eva_somatic and eva, respectively), gene2phenotype (gene2phenotype), PanelAPP (genomics_england), and Open Targets Genetics (ot_genetics_portal).

version : This is the version of the data retrieved from Open Targets Platform.

score : This is the minimum (and equal) value of the genetic association score threshold.

datap : This represents the input path. If not specified, the current directory will be used.

resultp : This represents the output path. If not specified, the current directory will be used.

Note: If ot_genetics_portal will be run, then variant_summary.txt file should be download into input folder.

Example running

To construct association data frames for version 21.04 of Gene2Phenotype without any threshold for genetic association score:

python3 scripts/01_association_evidence.py -source gene2phenotype -datap input/ -resultp output/ -version 21.04 -score 0.0

After constructing all association data frames for interested sources:

To prioritize the targets:

python3 scripts/02_target_prioritisation.py -datap input/ -resultp output/ -version 21.04

Output

Output files will be numbered:

  • 02 - Annotated association data frames for each source
  • 03 - GoF/LoF filtered association data frames for each source
  • 04 - Drug mode of mechanisms integrated association data frames for each source
  • 05 - Merged filtered association data frame
  • 06 - Merged filtered association data frame of validation set
  • 07 - Merged filtered target data frame (includes tractability)

Files including statistics will be created for representing total number of targets or associations.

Contact

It is a product of PhD rotation study of Cansu Dincer under the supervision of Dr Gosia Trynka, Dr Ian Dunham and Dr Mohd Karim from Open Targets, Wellcome Sanger Institute and European Bioinformatics Institute.

For any problems or feedback on ProGoF, you can contact here.

Terms and Conditions

Copyright (c) 2021 Genome Research Ltd.

Author: Cansu Dincer cd7@sanger.ac.uk

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program. If not, see http://www.gnu.org/licenses/.

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Retrieval of the disease association and evidence from the Open Targets Platform, annotation of the association evidence through Clinvar, Sequence Ontology and PanelApp APIs, and finally filter and prioritise the protective targets when they possess LoF.

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