Select menu: Stats | QTLs (linkage/Association) | QTL Analysis | Single Trait Association Analysis (Single Environment)
Use this to perform a mixed model marker trait association analysis (also known as linkage disequilibrium mapping). When testing for marker-trait association in a genetically diverse population, it is necessary to account for population structure, which introduces non independence between genotypes as a result of common genetic background.
- After you have imported your data, from the menu select
Stats | QTLs (linkage/Association) | QTL Analysis | Single-trait Association Analysis (Single Environment).
- Fill in the fields as required then click Run.
This lists data structures appropriate to the current input field. Double-click a name to copy it to the current input field or type the name. If data has been stored in a QTL data space then only the data structures present within that data space will be displayed in the Available data, otherwise all the current data within Genstat will be displayed. When data are present within the QTL data space you can right-click on the Available data list to open a shortcut menu where you can change between displaying data only within the data space and all data within Genstat.
Quantitative trait means
A variate specifying the quantitative trait (phenotypic) means for each genotype.
A factor specifying the genotype for each mean.
Marker genotype scores
A pointer specifying the marker scores. The pointer should contain a set of factors (one for each marker) where each factor has the same labels representing the genotype scores and the labels are all in the same order.
A factor defining the different linkage groups (or chromosomes).
Position within linkage group
A variate specifying the positions within linkage group for each marker.
A text specifying the names for each marker.
Labels for genotypes
A text specifying the labels of genotypes for the markers.
Specifies the model to account for genetic relatedness between genotypes.
|Eigenanalysis||Infers the underlying genetic substructure in the population by retaining the most significant principal components from the molecular marker matrix – the scores of the significant axes are used as covariables in the mixed model, which effectively is an approximation to the structuring of the genetic variance covariance matrix by a coefficient of coancestry matrix (kinship matrix).|
|Kinship matrix||Provides a space to supply a kinship matrix containing coefficients of coancestries that is to be included in the mixed model.|
|Subpopulation groupings||Provides a space to supply a factor of subpopulation groupings to be included in the mixed model.|
|Null||No correction is made for genetic relatedness.|
|Run||Run the association analysis.|
|Cancel||Close the dialog without further changes.|
|Options||Opens a dialog where additional options and settings can be specified for the analysis.|
|Defaults||Reset options to the default settings. Clicking the right mouse on this button produces a pop-up menu where you can choose to set the menu using the currently stored defaults or the Genstat default settings.|
|Store||Opens a dialog to specify names of structures to store the results from the analysis.|
|Pin||Controls whether to keep the dialog open when you click Run. When the pin is down the dialog will remain open, otherwise when the pin is up the dialog will close.|
|Restore||Restore names into edit fields and default settings.|
|Clear||Clear all fields and list boxes.|
|Help||Open the Help topic for this dialog.|