The second version of the Training School METHADA2020-eHandsOn: Management of transcriptomic metadata and data analysis, will take place from December 1st to 4th. José Tomás Matus is one of the organizers of the event and also one of the trainers. This time the course has the presence of more than 100 observers from around the world.
After the success of the First Version of METHADA, held at the I2SysBio in February 2020 and with representation from more than 10 European countries, its second version will be carried out in online format.
The rise of the latest technologies that combine physics, optics, chemistry and their application to molecular biology has led to high-throughput experiments, yielding an explosion of publicly available data. This data ranges from Next Generation Sequencing (NGS) to transcriptomics, phenomics, metabolomics to large scale single cell data.
In the case of transcriptomics, which generates to date the biggest amount of data compared to other omics, protocols for data submission are not fully standardized for grapevine data and not controlled by the research community. Public available gene expression datasets have a hidden true potential in the light of data reanalysis and integration. In line with the FAIR (Findable Accessible Interoperable Reusable) principles our next challenge as a community relies on correct sample and experiment annotations, using controlled vocabularies to ensure both human readability and computational tractability.
This online training course addresses the management and analysis of transcriptomics data, and is organized into three modules. In the first unit, students will work to learn how to correctly annotate experiments and manage metadata to standardize the upload of experiments to public repositories (such as SRA and ENA). Second, attendees will receive training in the use of the A.I.R. ('Artificial Intelligence RNA-seq', by Sequentia Biotech S.L.) for the management of transcriptomic data, including resources freely available to the grapevine community. Finally, students will learn to use the GREAT platform (GRapevine Expression ATlas) for the analysis of public transcriptomic data from the grapevine.
It is possible to participate as a course listener by accessing here.
