About

Matapax (Marker And Trait Analysis Pipeline And eXplorer) is an association pipeline currently targeted towards enabling fast and easy association mapping in Arabidopsis thaliana with an emphasis on intuitive and informative analysis. To achieve this aim, we have focused on several features. It ties together several tools used extensively in genome wide association studies (GWAS) and Arabidopsis SNP databases.

GAPIT (Buckler Lab) provides the association core of the pipeline. By using GAPIT, we are able to provide efficient mixed-model association with corrections for kinship and population structure. GAPIT uses state-of-the-art methods developed for statistical genetics, such as the unified mixed model, EMMA, the compressed mixed linear model, and P3D/EMMAx. Future versions of Matapax will include EMMAx.

AtPolyDB (Magnus Nordborg Lab) provides SNP data for 1307 accessions. The SNPs are determined using a 250k Affymetrix genotyping chip thus providing a high resolution map of genomic variation across a large number of species.

The 1001 Genomes Project provides SNP data for 84 accessions. The SNPs are determined through resequencing thus providing an extremely high resolution map of genomic variation. Currently only a few accessions are available. However, in future, this number will increase.

What data is suitable?

Any qualitative or quantitative data describing different traits. This can include physical measurements (eg. plant height, leaf length), metabolic measurements (sugar content, amino acid content) or microarray data. You should have around 20 genotypes that have been genotyped for statistical robustness. You can view which accessions are available here or when you choose your database during the initial setup for the pipeline, you'll be able to see immediately which of your genotypes match those in the marker databases.

Getting Started

We assume that you've already measured your traits and now have a matrix (or a single vector) of trait measurements for many genotypes. The next step is to go here to submit your data.