The following deliverables and reports summarise the work performed by Solve-RD partners.
D1.3 Training modules, guidance document and online help module for collection of phenotypes
In order to engage users with Solve-RD and facilitate their contribution of phenotypic data to the project, we have developed training materials and have carried out training activities, which will continue in time. We have set up a practical guide to PhenoTips data entry, provided an in-depth YouTube video with instructions, organized our first training webinar for ERNs (available here) and created an option for uploading phenotype data using an Excel template. In addition, further support to researchers is provided by one-to-one tele-conferences for PhenoTips usage and by answering any queries they have through email@example.com.
D1.4 Deployment of PhenoTips custom forms according to the ERNs specifications
This deliverable report describes the adaptations and customisations CNAG-CRG have carried out in PhenoTips to allow for the collation of phenotype data tailored to each ERN and disease group. Users can enter data individually for each proband and family member through one of the customized templates, import information using JSON schemas or provide a filled-in Excel template for bulk upload.
D1.5 Guidelines for collection of experimental data
This deliverable report provides information on the guidelines that have been developed for experimental data collection for Solve-RD. These guidelines aim to aid and facilitate all data upload from all Solve-RD collaborators and ensure high quality standards are met.
D2.3 Guidelines for Quality Control metrics
Solve-RD has collated over 8,400 standardised phenotypic and genomic datasets from partners across different ERNs and countries. To ensure best practices and standardisation of the process, HPO, OMIM and Orphanet (ORDO) ontologies are used to collect phenotypic data, and GATK best practices and GA4GH standards are followed in the collection and processing of genomic data through a standardised pipeline (Laurie et al., 2016 here).
As data submitted to Solve-RD for reanalysis has been sequenced at a variety of different centres, under different protocols and using different technologies it is fundamental to ensure a minimum quality of geno-pheno datasets to guarantee proper downstream analyses and results. Therefore, several quality control metrics have been established, and are now automatically performed for each of the samples entering the Solve-RD project.
Here we report on the established framework for quality assessment (processing checkpoints, genome coverage metrics, phenotypic data and sample relatedness) for RD-Connect and Solve-RD data and provide guidelines to enable Solve-RD data submitters and Data Analysis Task Force (DATF) members to easily assess the quality of the provided data and compare genomic datasets before undertaking further downstream analyses.
D3.8 First summer school for ePAGs delivered
This deliverable report covers the first edition of the EURORDIS Winter School, the capacity building training programme for rare disease patient representatives on scientific innovation and translational research, which was held at the Imagine Institute for Genetic Diseases in Paris from 19-23 March 2018.
D4.3 Central RD-Connect database serving Solve-RD, including user authentication and authorization
Solve-RD will employ the RD-Connect Genome-phenome Analysis Platform (GPAP) to pool and enable controlled access to a large number of harmonised and integrated datasets from unsolved rare disease cases. This deliverable report describes the actions taken to ensure GPAP is serving Solve-RD, including steps for user authentication and authorization and how researchers can share their data.
D4.5 Metadata catalog operational, with initial content
In order for the resources that are contributed to and will be developed during the Solve-RD project a discovery system was required. Such a system is being developed based on proven technologies and a suitable set of standards. This deliverable focuses on the building of an initial version of the system, based on the Café Variome platform, for asset discovery called RD-NEXUS (Rare Disease Network for EXploring the UNseen). In order to build the system, a working data model for an agreed set of parameters (termed 'findable facets’) was defined and integrated in to a data model. APIs allowing interoperability with other systems were also developed in collaboration with the GA4GH. Exemplar data have been processed and entered into the current RD-NEXUS system to illustrate its functionality and highlight any potential issues, before being demonstrated to potential users within the ERN networks. A complete first version of RD-NEXUS was thereby created, and is now available for demonstration and testing.
D4.7 All foundational standards selected and implemented across the project
Underpinning all activities at Solve-RD, from data submission, quality control, data dissemination to appropriate resources, discovery and finally distribution, a set of defined standards are required to ensure smooth and efficient data flow and interoperability between resources within Solve-RD and external resources. This deliverable focuses on defining and implementing the set of standards required to facilitate these processes, and here we describe how these standards have been established and implemented across Solve-RD.
D6.4 Solve-RD communication and dissemination tools
This deliverable report includes the Solve-RD communication and dissemination plans and describes the tools Solve-RD uses to implement both.