Virtual Training School in Transcriptomic Metadata Handling and Data Analysis
ATTENDANCE STATISTICS
PLENARY SESSIONS
DAY 1. OMICS DATA GUIDELINES & SUBMISSION
DAY 2. RNA-SEQ ANALYSIS. AN OVERVIEW.
DAY 3. GREAT DATABASE (GRape Expression ATlas)
DAY 4: TRAINING AIR (ARTIFICIAL INTELLIGENCE RNA-SEQ)
OVERVIEW
TITLE: METHADA 2020 eHands on – Virtual Training School in Transcriptomic Metadata Handling and Data Analysis
DATE: November 30th– December 4th 2020
BRIEF PROGRAM:
The rise of the latest technologies combining physics, optics, chemistry and its 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 providing correct sample and experiment annotations, using controlled vocabularies to ensure both human readability and computational tractability. This training school addresses genomics data handling and analysis, and it is organized in three modules.
On the first unit, trainees will work to learn how to use the guidelines provided by the INTEGRAPE community to correctly annotate experiments and submit them on public repository. We will explore standards and bio-ontologies for FAIR data annotation using their personal data.
The second module will teach the trainees how to use the tools from Sequentia (AIR for transcriptomics).
Finally, attendees will be introduced to the GREAT (GRapevine Expression ATlas) platform for transcriptomic meta-analysis. The GREAT platform is a good example of reusing publicly available RNA-seq data to answer new biological questions. Trainees will have the opportunity to explore the GREAT platform with their own list of genes of interest (15 genes max. in VCostv3 annotation see Canaguier et al., 2017).
Trainers:
Camille Rustenholz
INRAE
Amandine Velt
INRAE
Riccardo Aiese Cigliano
SEQUENTIA BIOTECH
José Tomás Matus
I2SysBio, Valencia
Jérôme Grimplet
CITA-Aragon.es
SELECTION CRITERIA OF TRAINEES
TRAINEE SELECTION NOW CLOSED AND COMPLETED
Evaluation of applications will be based on the following criteria:
Priority will be given to those with the correct criteria among PhD students, early career researchers and others from COST member countries as well as MC Observers from Near-Neighbouring countries. Those with correct criteria from non-COST countries are also encouraged to apply. COST eligibility details are available on pages 26/27 of the COST Vademecum.
Evaluation of applicants will be based on the following criteria:
– Postdocs, PhD students, PIs and bioinformaticians working with computational biology related to grapevine with high motivation in spreading these good practices learned during the training school. – Trainees must have transcriptomics or genomics data that they are planning to submit to public databases or already submitted data. – A maximum of 20 trainees will be selected but participation as observers are welcome
Selection of participants will be made by COST Integrape local organisers on the basis of all submitted data:
Reason for participating
Curriculum vitae
The training school is free to attend, but as the training school will be online, travel expenses will not be reimbursed.
CONTACTS
Dr José Tomás Matus
Institute for Integrative Systems Biology Carrer del Catedràtic Agustín Escardino Benlloch, 46980 Paterna, València tomas.matus@uv.es
Dr Jérôme Grimplet
Centro de Investigación y Tecnología Agroalimentaria de Aragón Avda. Montañana 930 50059 – Zaragoza Phone: +34 976 71 3635 jgrimplet@cita-aragon.es
PROGRAM
Each module will include a plenary session and a training session, each around 2 hours. The plenary sessions of Modules 1 and 3 will be organized in the morning with all trainees and open to additional observers. The training sessions will occur the next two afternoons and divided into 2 groups of 10 trainees each. Module 2 will involve the plenary session on the Wednesday morning (open to Observers) and the training session on the Friday morning (Trainees only). The program can be visualised here.
Module 1: INTEGRAPE guidelines for OMICS data submission
Session 1 (December 1st morning) PLENARY: -Plenary session for trainees and observers: presentation of the INTEGRAPE guidelines for sequencing data submission at ENA
Session 2 (December 1st or 2nd afternoons) TRAINING: -Guided practices onto submitting metadata at ENA for trainees using their own data.
Module 2: The AIR platform for RNAseq data analysis.
Session 1 (December 2nd morning) PLENARY: – Next Generation Bioinformatics: making NGS data analysis accessible – Brief introduction to RNA-seq data analysis methods and to AIR online data analysis platform – Registration to AIR – Data upload and how-to setup an analysis
Session 2 (December 4th morning) TRAINING: – RNA-seq data visualization and exploration with AIR
Module 3: The GREAT platform for expression data analysis
Session 1 (December 3rd morning) PLENARY: -Plenary session for trainees and observers. Presentation of the GREAT database of RNAseq data for meta-analysis.
Session 2 (December 3rd or 4th afternoons) TRAINING: -Guided practices for trainees on using the database