USARC 10X Genomics Single Cell DNA Sequencing Data
We investigated the impact of ploidy heterogeneity on copy number inference at a single cell level using fluorescence-activated cell sorted (FACS) nuclei from an undifferentiated soft tissue sarcoma. FACS revealed the presence of three aberrant subpopulations, including a haploid, a near diploid and a whole genome doubled population. Once sorted, single cell nuclei underwent whole genome sequencing using the chromium CNV single cell DNA library kit (10X Genomics). We sequenced single normal nuclei (2n) and single aberrant / tumour nuclei (1n, 2n and 2n+).
- 4 samples
- DAC: EGAC00001002610
- Technology: Illumina HiSeq 4000
1. Policy Background 1.1 Definition of research data Data are defined as facts, observations or experiences on which an argument or theory is constructed or tested. Data may be numerical, descriptive, aural or visual. Data may be raw, abstracted or analysed, experimental or observational. Data include but are not limited to: laboratory notebooks; field notebooks; questionnaires; texts; audio files; video files; models; photographs; test responses. UCL staff and students routinely create data as part of the research workflow. These outputs represent the evidence that underpins academic endeavours and in conjunction with publications, form an important aspect of the scholarly record. 1.2 Research Data Management Research Data Management (RDM) covers the decisions made during the research data lifecycle to handle the outputs of your research projects from the planning stage through to preserving and sharing your outputs1. The research data lifecycle comprises of four phases: 1) output management planning; 2) active research phase; 3) archiving, preserving and curating; and 4) discovery, access and sharing. Harnessing the advantages of an open working environment serves to disseminate research findings more quickly and facilitates even greater collaboration. RDM is an essential enabler of Open Science and Scholarship2 – the practice of making research outputs and the research process available to as wide an audience as possible across the research data lifecycle. 1.3 Challenges Advances in technology have enabled the exponential growth in the creation of data, which in turn has led to both novel methods for conducting research (data-driven research) and a new, significant data management burden. However, there are challenges to managing research outputs that can be broadly categorised into the following: a) cultural factors such as a lack of awareness and incentives to engage with the principle of Open Science; b) technical factors such as a lack of/inaccessible infrastructure providing access to research outputs in a controlled and mediated way to maximise research benefits; c) organisational issues – the need for even greater advice and advocacy to educate and guide; and d) financial constraints – sufficiently allocating resources to cover the cost of RDM to further support researchers when engaging with the principle of Open Science and Scholarship. 2. Purpose The purpose of this Policy is to provide a framework to define the responsibilities of UCL staff and research students in managing their data. This in turn will facilitate the maintenance and preservation of research data as a first class research object in its own right, making them available to the widest possible audience for the highest possible impact. This policy is intended to ensure that research data created as part of the research process are FAIR - Findable, Accessible, Interoperable and Reusable 3. Data should be: Accurate, complete, authentic and reliable; Attributable and citable; Identifiable, retrievable and available with minimal barriers; Secure from loss and degradation; Retained for a minimum of ten years4 after publication or public release; Compliant with legal obligations, ethical responsibilities and the rules of funding bodies. 3. UCL commitment UCL recognises that appropriate management of research data leads to an enhanced research practice respecting specialist knowledge, supporting synthesis of new knowledge and facilitating collective and collaborative working practices in order to gain wisdom5. Further, UCL considers the research data generated by its members as a valuable research output, an asset to the institution and a critical contribution to the knowledge economy6. UCL is therefore fully committed to ensuring that all staff and research students receive support in managing their data -and other research outputs- across the research data lifecycle. 4. Policy statements 4.1 Ensure data are as open as possible, as closed as necessary7. UCL staff and research students should safeguard data appropriately by applying data access restrictions where necessary and that are in-line with the nature and complexity of the data. UCL should enable its staff and research students to fulfil the requirements of good research practice by enabling them to manage research data in a manner that maximises data impact and acknowledges the value of data as a primary research outputs, whilst in the most open manner appropriate8. 4.2 Share responsibility for managing and preserving research data between all members of UCL. Section 5 outlines responsibilities of UCL staff and research students and makes recommendations for managing research data. 4.3 Following primary use (e.g. publication) or when research data is archived for longer-term preservation, these data will be made available in a timely fashion. UCL staff and research students should utilise research domain-specific archives and repositories where possible. This enables staff and research students to benefit from specialist infrastructures to manage the data. Staff and research students may also use generic repositories such as the UCL Research Data Repository9 to fulfil this requirement. Data must be made available in a timely fashion and not kept from being open longer than is necessary. 4.4 Establish clear lines of responsibility so that research data generated at UCL will always have an owner who is responsible for preserving research data. If the original owner of the data is no longer affiliated with UCL, the data retained by UCL will continue to have an owner to steward its maintenance and preservation. 4.5 All research datasets - regardless of where they are archived and how open10 they are - should be recorded in UCL Research Publications Services11 or the UCL Research Data Repository. In recording the location of these data and their level of openness, UCL staff and research students will comply with all national and many international policies and requirements from funders of academic research. 5 Responsibilities and recommendations 5.1 All UCL Staff and research students All UCL staff and research students should create data management plans to document how they will manage their data across the research data lifecycle12. All staff and research students should: 1. Develop and record appropriate procedures and processes to collect, store, use, reuse, access and retain research data associated with their research program; 2. Establish and document agreements for managing research data when involved in a joint research project, collaborative research, or research undertaken in accordance with a contractual agreement; 3. Include within research grant proposals appropriate consideration of the cost and time implications of data storage and management; 4. Ensure that the integrity and security of their data is maintained; 5. Be aware of their obligations and potential liability when handling data protected by the UK Data Protection Act (2018), European General Data Protection Regulation (2018) and any other applicable data protection legislation13; 6. Plan for the on-going custodial responsibilities for the research data at the conclusion of the research project or on departure from UCL; 7. Include recommendations for the destruction of research data (if required) to the designated departmental data steward, or, where no such role exists, the Head of Department or Research unit; 8. Create a record of their research datasets in either the UCL Research Publications Services14 or UCL Research Data Repository15 Researchers are also encouraged to get an ORCID or any equivalent unique personal identifier that unambiguously indicates the author of a research output16. Such identifier helps them record and report their work; it can be used in publications, grant applications, and in UCL's Research Publications Service. 5.1.1 Research students and supervisors Embedding RDM best practice in early career research is critical to establishing an effective data management ethos. Good research practice requires research students and their supervisor to plan the collection, storage, security and use of research data, in accordance with conventions in their fields of study and (if applicable) obligations from their funders. In addition to the recommendations made in 5.1, research students and supervisors should: 1. Ensure that their plans and activities are documented in accordance with their obligations as defined by relevant funding bodies and UCL policies. 2. Supervisors should encourage their research students to fill out a Data Management Plan17 5.1.2 Heads of Department or Research Units In addition to the recommendations made in 5.1, heads should: 1. Promote best practice in all aspects of research including Research Data Management. They should ensure that staff and students are aware of their responsibilities and obligations. 2. Assume stewardship of data once the researchers involved in compiling that data leave UCL. Heads can delegate stewardship to a dedicated data steward. 3. Identify and implement any training or skills development required by researchers to execute their responsibility. 4. Authorise procedures adopted by staff and student researchers (following consultation with their supervisor) for the collection, storage, use and, if required destruction, of their research data. 5. Establish and implement departmental procedures for the storage and retention of research data in line with UCL policy or legislative obligation. 6. Ensure staff and research students conducting human research are aware of, and appropriately trained in, all of their responsibilities and obligations relating to research data collected in the course of their research. 7. Ensure questions relating to data compiled by members of their department can be addressed; particularly those relating to appropriate retention periods, access permissions, and any restrictions that should be applied to re-use and repurpose existing data. 5.2 UCL Research Data Services and UCL Library Services UCL Research Data Services and UCL Library Services are responsible for providing guidance and support relating to good Research Data Management practice. Together, both teams can advise researchers on: Planning and writing data management plans; Identifying and understanding research funders’ requirements; Depositing, sharing and citing research datasets in external and local repositories; Storing, transferring, and processing data. 5.2.1 UCL Research Data Services UCL recognises the strategic importance of providing services to manage and preserve research data and is committed to supporting a permanent team within the centralised ISD organisation that will create and support institutional services for all UCL researchers. Therefore, UCL Research Data Services team is responsible for providing large scale, high performance networked storage for research projects and longer-term storage facilities for the preservation and dissemination of UCL research data. The UCL Research Data Services18 team provide flexible, resilient, responsive, and cost effective data management facilities and support, in particular: The Research Data Storage Service providing research projects with terabyte-scale shared storage19; The UCL Research Data Repository20 for any data which must be archived and preserved beyond the end of a project The UCL Research Data Services Team also provide advice on technical solutions for Research Data Management and associated policies. 5.2.2 Research Data Management Team UCL Library Services provides a dedicated Research Data Management21 advisory service for all UCL staff and students. The Research Data Management team22 can advise on managing research data – across the research data lifecycle – and in line with best practice, UCL and funders’ expectations. The team also provides first line/administrative support including training for the UCL Research Data Repository. For support and advice, contact the RDM team: Research Data Management team: email@example.com o Kirsty Wallis - Head of Research Liaison o Dr Christiana McMahon & Dr James Houghton – Research Data Support Officers 5.3 UCL Research Information and IT Services (RIISG) UCL Research Information and IT Services Group is accountable for maintaining and updating the Research Data Policy. They ensure that new developments and evolving best practice is reflected in the policy. 5.4 Vice Provost (Research) UCL’s Vice-Provost (Research) is responsible for overseeing the implementation of the UCL Research Data Policy and ensuring that UCL complies with funder requirements and academic needs for Research Data Management. 5.5 Provost The Provost, as senior Executive Officer in UCL, in conjunction with the Vice-Provost (Research) and UCL’s Senior Management Team, is accountable for ensuring that UCL’s policy for, and practice of, Research Data Management is fit for purpose. 6 Policy Implementation and Review Procedures This policy will not supersede any other UCL policy. If it directly conflicts with research funders’ policies, the latter will take precedence. The Vice-Provost (Research) is ultimately responsible for ensuring that both divisional and central resources are sufficient for compliance with this policy. The Pro-Vice-Provost (UCL Library Services) and the UCL Records Manager are together responsible for co-ordinating the implementation of the policy. This policy will be reviewed at least every 3 years by the UCL Office for Open Science.
Studies are experimental investigations of a particular phenomenon, e.g., case-control studies on a particular trait or cancer research projects reporting matching cancer normal genomes from patients.
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