The objective of the Plant A+ project is to cross data from different domains: phenomics, genetics and environmental data and develop tools to integrate, analyse and visualize these data in a FAIR manner. Nowadays, mother genomes are available and shared, and a high amount of phenotypic data is produced daily. This project is a collaboration between ISBE, EMPHASIS and ELIXIR and aims to improve data harmonisation and standards to better re-use and integrate the existing data in plant science.
With this project, this demonstrator developed a series of interesting tools that should improve best practices and FAIR data sharing in plant sciences.
FAIRdom SEEK
The FAIRdom SEEK tool was developed to bring data harmonisation and standards by capturing FAIR metadata to handle both genomic and phenomics data. With FAIRdom SEEK, each dataset entry includes biological material description, plant phenotyping ontologies and methods, phenotyping dataset and experiments location but also allows for custom metadata to be added depending on the need.
pISA-tree
Complementary to FAIRdom SEEK called pISA-tree was developed. pISA-Tree is a system of batch files that creates a standard directory tree and automatically guides the user through required metadata inputs and is more adapted to the needs in small labs.
Gene Expression Plotter
Another tool was developed to facilitate the analysis and the visualisation of gene expression data. This tool already publicly available via github makes RNA sequencing expression data and data visualisation available via the browser. It facilitates sharing, and exploration of the data and provides non-technical researchers with powerful visualisation tools to quickly analyse and generate graphical data representation.
Find the tool here: usadellab.github.io/GeneExpressionPlots
and on github: https://github.com/usadellab/GeneExpressionPlots
INRA (Cyril Pommier)
FZJ (Asis Hallab, Björn Usadel, Constantin Eiteneuer)
UNIMAN (Stuart Owen)
NIB (Kristina Gruden)
Papoutsoglou et al (2020) Enabling reusability of plant phenomic datasets with MIAPPE 1.1. New Phytologist, DOI: https://doi.org/10.1111/nph.16544
Photo credit: Filippo Vurro, IMEM-CNR, EMPHASIS Photo Competition 2020