Work Package 1 – Wet lab
Objectives: Methods to measure Glycomics and methods to link and integrate genetics, epigenetics and glycans
D1.1 : MS methods [M36] – Report on novel High Throughput MALDI-TOF-MS approach for protein and site specific glycosylation profiling
D1.2 : Algorithms for feature extraction [M36] – Report on algorithm to extract features
D1.3 : Data quality guideline [M48] – Report on work flow to standardize data handling and improve quality of the data
D1.4 : Report on epigenetic analysis [M48] – Report on the results of the analysis of epigenetic regulation of the GWAS hits relevant for IgG glycosylation
D1.5 : Report on genetic analysis [M48] – Results of the advanced genetic analysis to study association between multiple genetic variants and Glycans
Work Package 2 – Data Science
Objectives: Development of tailor-made statistical and bioinformatics methodology
D2.1 : Methods and software of network analysis [M48] – Network-based methods for multiple omics data analysis and software tools enabling application of the methods
D2.2 : Report on methods for integrative analysis [M48] – Latent variable methods for integration of high dimensional datasets and probabilistic versions of these approaches
D2.3 : Report on measurement error analysis [M48] – Methods to account for measurement error when using summaries of the data.
D2.4 : Report on survival analysis [M48] – Extensions of parametric survival models for clustered data subject to delayed entry.
D2.5 : Report on integrated omics analysis for ageing [M48] – Results and Interpretation of the system medicine analysis of multiple datasets in centenarians
D2.6 : Report on integrated omics analysis for CWP and ageing [M48] – Results and Interpretation of large scale data analysis methods to TwinsUK with regard to CWP and ageing
D2.7 : report on genetic analysis of Glycans [M48] – Two types of methods will be used to identify association between rare genetic variants and glycans, namely imputation of rare variants using whole genome sequencing data and genomics sharing in population with high kinship coefficients. The deliverable concerns the output of application of these methods to available datasets.
Work Package 3 – Training
Objectives: To provide training for the next generation of inter- and multi-disciplinary researchers
D3.1 : Individual research projects descriptions [M18] – Update of the ESR projects to the current scientific developments
D3.2 : Personal career development plans for all ESRs [M18]
D3.3 : Policy document on training courses for wet and dry lab researchers [M42] – IMforFUTURE will contribute to training outside the consortium by producing a vision document on
multidisciplinary training in omics research
D3.4 : Report on the integrated workshop [M42] – This workshop will be interdisciplinary and will be organized by the ESRs. The ESRs will work together on the same consortium datasets: some of the ESRs will generate and process new data for these studies, others will apply novel statistical and bioinformatics approaches and finally ESRs will be involved in interpretation of the results. All ESRs will present and discuss their work on these datasets in the workshop
D3.5 : PhD thesis titles & degrees [M48]
Work Package 4 – Impact
Objectives: To disseminate to the general public the developed methods, tools and findings of IMforFUTURE and to arrange public engagement activities.
D4.1 : Report on outreach activities first year of projects [M24]
D4.2 : Description of all training modules which are open for researchers outside the consortium [M36]
D4.3 : Report on the outreach activities in the second year of the ESR projects [M36]
D4.4 : Report on the outreach activities in the third year of the ESR projects [M48]
D4.5 : Website with an overview of all developed methods within IMforFUTURE together with links to software or code (dissemination) [M48]
Work Package 5 – Efficient management and coordination of IMforFUTURE
Objectives: Efficient management and coordination of IMforFUTURE
D5.1 : Launch of IMforFUTURE website (part of the website will only be accessisble for consortium members for exchange of documents, minutes, etc) [M3]
D5.2 : Recruitment strategy in place [M6]
D5.3 : Consortium agreement [M2]
D5.4 : Data management plan for the datasets which will be used within IMforFUTURE [M6]
D5.5 : Report on the network activities which have taken place [M48]
D5.6 : Supervisory board of the network in place [M2]
D5.7 : Progress report on the first 12 months of the project [M13]
D5.8 : Mid term report [M22]
Work Package 6 – Ethics requirements
Objectives: To ensure compliance with the ‘ethics requirements’ set out in this work package.
D6.1 : HCT – Requirement No. 1 [M6]
1. For all human cells/tissues, a description of type and origin must be provided.
2. In case human cells/tissues are obtained within another project, details on cells/tissues type and authorisation by primary owner of data (including references to ethics approval) must be provided. 3. In case of human cells/tissues stored in a biobank, details on cells/ tissues type must be provided, as well as details on the biobank and access to it.
D6.2 : POPD – Requirement No. 2 [M6]
1. Please describe what kind of data will be collected and their source(s). In case the project will use data sets with personal information, a description of the character of these data sets and their origin must be provided.
2. Confirm that the use of personal information in this project is covered by the informed consent related to the primary collection of data. Please provide templates of information sheets and informed consent.
3. If applicable, copies of authorizations of the relevant authority and/or ethics committees must be provided.
4. Copies of opinion or confirmation by the competent Institutional Data Protection Officer and/or authorization or notification by the National Data Protection Authority must be submitted (which ever applies according to the Data Protection Directive (EC Directive 95/46, currently under revision, and the national law). 5. Detailed information must be provided on the procedures that will be implemented for data collection, storage, protection, retention and destruction and confirmation that they comply with national and EU legislation.