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Considerations when processing and interpreting genomics data of the placenta.

ABSTRACT: The application of genomic approaches to placental research has opened exciting new avenues to help us understand basic biological properties of the placenta, improve prenatal screening/diagnosis, and measure effects of in utero exposures on child health outcomes. In the last decade, such large-scale genomic data (including epigenomics and transcriptomics) have become more easily accessible to researchers from many disciplines due to the increasing ease of obtaining such data and the rapidly evolving computational tools available for analysis. While the potential of large-scale studies has been widely promoted, less attention has been given to some of the challenges associated with processing and interpreting such data. We hereby share some of our experiences in assessing data quality, reproducibility, and interpretation in the context of genome-wide studies of the placenta, with the aim to improve future studies. There is rarely a single "best" approach, as that can depend on the study question and sample cohort. However, being consistent, thoroughly assessing potential confounders in the data, and communicating key variables in the methods section of the manuscript are critically important to help researchers to collaborate and build on each other's work.

SUBMITTER: Konwar C

PROVIDER: S-EPMC6612459 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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Considerations when processing and interpreting genomics data of the placenta.

Konwar Chaini C Del Gobbo Giulia G Yuan Victor V Robinson Wendy P WP

Placenta 20190107

The application of genomic approaches to placental research has opened exciting new avenues to help us understand basic biological properties of the placenta, improve prenatal screening/diagnosis, and measure effects of in utero exposures on child health outcomes. In the last decade, such large-scale genomic data (including epigenomics and transcriptomics) have become more easily accessible to researchers from many disciplines due to the increasing ease of obtaining such data and the rapidly evo ...[more]

PMID: 30642669

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Project description:BackgroundThe emergence of high throughput technologies that produce vast amounts of genomic data, such as next-generation sequencing (NGS) is transforming biological research. The dramatic increase in the volume of data, the variety and continuous change of data processing tools, algorithms and databases make analysis the main bottleneck for scientific discovery. The processing of high throughput datasets typically involves many different computational programs, each of which performs a specific step in a pipeline. Given the wide range of applications and organizational infrastructures, there is a great need for highly parallel, flexible, portable, and reproducible data processing frameworks. Several platforms currently exist for the design and execution of complex pipelines. Unfortunately, current platforms lack the necessary combination of parallelism, portability, flexibility and/or reproducibility that are required by the current research environment. To address these shortcomings, workflow frameworks that provide a platform to develop and share portable pipelines have recently arisen. We complement these new platforms by providing a graphical user interface to create, maintain, and execute complex pipelines. Such a platform will simplify robust and reproducible workflow creation for non-technical users as well as provide a robust platform to maintain pipelines for large organizations.ResultsTo simplify development, maintenance, and execution of complex pipelines we created DolphinNext. DolphinNext facilitates building and deployment of complex pipelines using a modular approach implemented in a graphical interface that relies on the powerful Nextflow workflow framework by providing 1. A drag and drop user interface that visualizes pipelines and allows users to create pipelines without familiarity in underlying programming languages. 2. Modules to execute and monitor pipelines in distributed computing environments such as high-performance clusters and/or cloud 3. Reproducible pipelines with version tracking and stand-alone versions that can be run independently. 4. Modular process design with process revisioning support to increase reusability and pipeline development efficiency. 5. Pipeline sharing with GitHub and automated testing 6. Extensive reports with R-markdown and shiny support for interactive data visualization and analysis.ConclusionDolphinNext is a flexible, intuitive, web-based data processing and analysis platform that enables creating, deploying, sharing, and executing complex Nextflow pipelines with extensive revisioning and interactive reporting to enhance reproducible results.

Project description:BackgroundBiobanking and genomic research requires collection and storage of human tissue from study participants. From participants' perspectives within the African context, this can be associated with fears and misgivings due to a myriad of factors including myths and mistrust of researchers. From the researchers angle ethical dilemmas may arise especially with consenting and sample reuse during storage. The aim of this paper was to explore these ethical considerations in the establishment and conduct of biobanking and genomic studies in Africa.MethodsWe conducted a narrative synthesis following a comprehensive search of nine (9) databases and grey literature. All primary research study designs were eligible for inclusion as well as both quantitative and qualitative evidence from peer reviewed journals, spanning a maximum of 20 years (2000-2020). It focused on research work conducted in Africa, even if data was stored or analysed outside the region.ResultsOf 2,663 title and abstracts screened, 94 full texts were retrieved and reviewed for eligibility. We included 12 studies (7 qualitative; 4 quantitative and one mixed methods). Ethical issues described in these papers related to community knowledge and understanding of biobanking and genomic research, regulation, and governance of same by research ethics committees, enrolment of participants, types of informed consents, data collection, storage, usage and sharing as well as material transfer, returning results and benefit sharing. ca. Biospecimen collection and storage is given in trust and participants expect confidentially of data and results generated. Most participants are comfortable with broad consent due to trust in researchers, though a few would like to be contacted for reconsenting in future studies, and this would depend on whether the new research is for good cause. Sharing data with external partners is welcome in some contexts but some research participants did not trust foreign researchers.ConclusionBiobanking and genomic studies are a real need in Africa. Linked to this are ethical considerations related to setting up and participation in biobanks as well as data storage, export, use and sharing. There is emerging or pre-existing consensus around the acceptability of broad consent as a suitable model of consent, the need for Africans to take the lead in international collaborative studies, with deliberate efforts to build capacity in local storage and analysis of samples and employ processes of sample collection and use that build trust of communities and potential study participants. Research ethics committees, researchers and communities need to work together to work together to adapt and use clearly defined ethical frameworks, guidelines, and policy documents to harmonize the establishment and running of biobanking and genomic research in Africa.

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Considerations when processing and interpreting genomics data of the placenta.

Publications

Considerations when processing and interpreting genomics data of the placenta.

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