All eQTL patterns for a single trait
Cis-trans plot per experiment
Genes peaking at a locus
Correlated QTL patterns

Methods

eQTL profiles mapped in the original papers are used for visualization and investigation, except for those found in Lowry et al. 2013 which were re-mapped from the original genotypes and gene expression data by a single marker model using a linear model in R.

Correlation

All pairwise correlations between eQTL patterns were calculated using the Pearson correlation coefficients between the eQTL patterns of genes within an experiment using the R function ‘cor’, on the LOD scores.

Mapping

The markers are mapped according to the original publications. The physical positions of the markers were used to compare and integrate the genetic maps of the different populations and can be obtained from the AraQTL homepage.

LOD score threshold

The LOD score thresholds are taken from the corresponding papers. Original determined genome-wide threshold levels may be applied to call significant eQTLs. The thresholds for comparing eQTLs will vary depending on the number of genes, eQTLs and populations involved.

Software

AraQTL was implemented in the Python Django web framework using a MySQL database backend. The web pages include Javascript, using JQuery, and the d3 and bootstrip libraries. The cis/trans plot and QTL profile plots built upon work by Karl Broman (Broman, 2015).