MaizeGDB is a community-oriented, long-term, federally funded
informatics service to researchers focused on the crop plant and
model organism Zea mays.
MaizeGDB is a founding member of
AgBioData,
a consortuim of agriculture-related online resources which is
committed to making agriculture-related research data FAIR.
GCV: A web-app that visualizes genomic context data in a single, federated interface by using functional annotations as a unit of search and comparison.
PAST: the Pathway Association Study Tool assigns your SNPs to genes and your genes to metabolic pathways. PAST transfers the attributes of your SNPs (R2, p) to the genes and identifies pathways that are significantly associated with your trait of interest.
By running PAST, either through the Shiny application or through the R console, researchers can gain a deeper understanding of the biological meaning of their GWAS results by investigating the metabolic pathways involved.
How to run PAST at MaizeGDB
MaizeGDB has three instances of PAST installed on R Shiny servers. There is a limit to running one job per server. If a link is unresponsive, please try a different server or check back later when the server becomes available. An average job takes between 30 - 90 minutes to complete.
Li et al. 2019. Leveraging GWAS data to identify metabolic pathways and networks involved in maize lipid biosynthesis. Plant J, 98:853-863
Warburton et al. 2017. Genome-wide association and metabolic pathway analysis of corn earworm resistance in maize. TPG: doi: 11:170069.
Tang et al. 2015. Using genome-wide associations to identify metabolic pathways involved in maize aflatoxin accumulation resistance. BMC Genomics 16:673.