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. 2019 Jan 8;47(D1):D1056-D1065.
doi: 10.1093/nar/gky1133.

Open Targets Platform: new developments and updates two years on

Denise Carvalho-Silva  1   2 , Andrea Pierleoni  1   2 , Miguel Pignatelli  1   2 , ChuangKee Ong  1   2 , Luca Fumis  1   2 , Nikiforos Karamanis  1   2 , Miguel Carmona  1   2 , Adam Faulconbridge  1   2 , Andrew Hercules  1   2 , Elaine McAuley  1   2 , Alfredo Miranda  1   2 , Gareth Peat  1   2 , Michaela Spitzer  1   2 , Jeffrey Barrett  2   3 , David G Hulcoop  2   4 , Eliseo Papa  2   5 , Gautier Koscielny  2   4 , Ian Dunham  1   2
Affiliations

Open Targets Platform: new developments and updates two years on

Denise Carvalho-Silva et al. Nucleic Acids Res. .

Abstract

The Open Targets Platform integrates evidence from genetics, genomics, transcriptomics, drugs, animal models and scientific literature to score and rank target-disease associations for drug target identification. The associations are displayed in an intuitive user interface (https://www.targetvalidation.org), and are available through a REST-API (https://api.opentargets.io/v3/platform/docs/swagger-ui) and a bulk download (https://www.targetvalidation.org/downloads/data). In addition to target-disease associations, we also aggregate and display data at the target and disease levels to aid target prioritisation. Since our first publication two years ago, we have made eight releases, added new data sources for target-disease associations, started including causal genetic variants from non genome-wide targeted arrays, added new target and disease annotations, launched new visualisations and improved existing ones and released a new web tool for batch search of up to 200 targets. We have a new URL for the Open Targets Platform REST-API, new REST endpoints and also removed the need for authorisation for API fair use. Here, we present the latest developments of the Open Targets Platform, expanding the evidence and target-disease associations with new and improved data sources, refining data quality, enhancing website usability, and increasing our user base with our training workshops, user support, social media and bioinformatics forum engagement.

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Figures

Figure 1.
Figure 1.
Interactive visualisation of protein–protein interactions in dedicated target profile pages.
Figure 2.
Figure 2.
Similar targets are displayed as an interactive visualisation (A) in the target profile page. By selecting a target, the view gets updated to show the diseases shared between any two targets (B). Clicking on any of the shared diseases reveals the underlying evidence (e.g. Genetic associations, Drugs, Text mining, Animal models) that supports the association between a disease and its two selected targets.
Figure 3.
Figure 3.
RNA and protein expression data are displayed side by side for easy comparison of target expression levels in healthy human tissues. (A) Each horizontal bar representing a tissue, e.g. Intestine, can be expanded to provide a detailed breakdown of expression in different parts of the tissue/organ, such as ‘Vermiform appendix’ and ‘Duodenum’ (B).
Figure 4.
Figure 4.
An additional visualisation to summarise expression data is also available, depicting gene expression variability in GTEx data.
Figure 5.
Figure 5.
The new visualisation in the ‘Bibliography’ section of target and disease profile pages. Both titles (A) and abstracts (B) are available and can be filtered by selecting one of the ‘chips’ at the top of the table. A drop-down menu is also available to allow selection of publications according to the available (biological) concepts, genes, diseases, drugs, journals and authors.
See this image and copyright information in PMC

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