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Welcome to RicePilaf, a post-GWAS/QTL analysis dashboard for rice genomes.

As the number of genome-wide association studies (GWAS) and quantitative trait loci (QTL) mappings in rice continues to grow, so does the already-long list of genomic loci associated with important agronomic traits. Unraveling the biological mechanisms that tie the GWAS regions and QTLs to the trait of interest is challenging, especially since it requires collating functional genomics information about the loci from multiple, disparate data sources.

RicePilaf takes as input a set of genomic intervals obtained from QTL analysis or from LD-based clumping of significant GWAS SNPs. It then provides functional insights into rice QTLs and GWAS loci by integrating:

• Pangenomic information from high-quality genome builds of multiple rice varieties
• Co-expression information from genome-scale co-expression networks
• Ontology and pathway information
• Regulatory information from rice transcription factor databases
• Epigenomic information from multiple high-throughput epigenetic experiments
• Text-mining information extracted from scientific abstracts linking genes and traits

Go to the Pages sidebar on your right to find information on installation, usage, feature addition, deployment, etc.

It is advised to install the app locally, especially for higher computational loads. Alternatively, you can try RicePilaf at one of the sites below:

URL	Site	Version	Status (Date)
https://ricepilaf.bioinfodlsu.com/	Contabo (Germany)	1.0.9	Running (August 27, 2024)
https://ricepilaf.irri.org/ https://rice-pilaf.irri.org/	Philippine Government Department of Science and Technology – Advanced Science and Technology Institute (DOST-ASTI) COARE – Science Cloud resource	1.0.3	Running (July 14, 2024)
http://136.239.215.114:11001/	Dr. Andrew L. Tan Data Science Institute, De La Salle University	1.0.6	Sever maintenance (Sept 5, 2024)
https://ricepilaf.ird.fr/	French National Research Institute for Sustainable Development	1.0.3	Running (July 14, 2024)