The
Q-K Mixed Model
process
tests for
association
between various types of
traits
and SNP
genotypes
or
alleles
from a single
SNP
at a time while adjusting simultaneously for population structure and family relatedness (Yu et al. 2006). You must already have computed the Q and K matrices. Two types of analyses can be performed: an
ANOVA
based on SNP genotypes or a
regression
testing for a linear trend of SNP alleles.
P-values
from these tests, with adjustments applied if requested, are plotted along the marker map.
One data set, the
Input Data Set
, which contains all of the marker data, is needed for this process. The sample data set used in the following example, the
samplegmdata_numgeno_rm_pcm.sas7bdat
data set, which was generated from the
samplegmdata.sas7bdat
described in
Sample Genetic Marker Data
, contains a root
identity-by-descent
(IBD) matrix computed for 60 computer-generated SNP genotypes by
single value decomposition
(SVD) from the
Relationship Matrix
process, a compressed IBD matrix from the
K Matrix Compression
process, a
principal components
matrix from the
PCA for Population Stratification
process, a coordinates matrix from the
Multidimensional Scaling
process, and a population membership probability, all merged with the original data. This data set is partially shown below. Note that this is a wide data set; markers are listed in columns, whereas individuals are listed in rows.
A second, optional, data set is the
Annotation Data Set
. This data set contains information, such as gene identity or chromosomal location, for each of the markers. The
annotation data set
used in this example, the
samplemap.sas7bdat
data set, was computer generated and identifies markers, locations, and gene identities. A portion of this data set is illustrated below. This data set is a tall data set; each row corresponds to a different marker.
Both data sets are included in the
Sample Data
folder that comes with JMP Genomics.