Large scale genetic mapping studies seek to associate genetic markers, such as
SNPs
, of known location, with various quantitative and qualitative phenotypic
traits
.
Marker-Trait Association
tests for association between various types of traits and marker
genotypes
or
alleles
from a single marker at a time.
The
Marker-Trait Association
process can perform either an
ANOVA
based on marker genotypes or a
regression
testing for a linear trend of marker alleles. Adjustments can be made for quantitative
covariates
and
random effects
or for some trait types,
strata variables
.
P-values
from these tests, with adjustments (including for Q and K matrices representing population structure and relatedness, respectively) applied if requested, are plotted along the marker map.
See the
MIXED
,
GLIMMIX
,
LOGISTIC
, and
PHREG
procedures in the SAS/STAT User's Guide for more information.
Note
:
Large scale genetic mapping studies frequently require the use of very large data sets. Analysis using the
Marker-Trait Association
process often takes an inordinate amount of time and computer resources. When analyzing SNPs or multiallelic markers that can be treated as SNPs based on the most frequent allele, you should consider using the
SNP-Trait Association
process.
One data set is needed for this process. The
Input Data Set
, contains all of the marker data and other effects needed for
association
testing. The computer-generated
samplegmdata.sas7bdat
data set, described in
Data Sets Used in JMP Genomics Processes
, was modified using the
Kinship Matrix
process, as described, to generate the
samplegmdata_kmx.sas7bdat
data set. The
samplegmdata.sas7bdat
data set, which is shown below, consists of 1000 rows of individuals with 130 columns corresponding to marker data on these individuals. This data set also contains 7 columns appended to the end, by the
Kinship Matrix
process, which list the coefficients from the
Cholesky
root of
each
pedigree
covariance matrix
. These
coefficients are used in the following association example as random effects in order to analyze family data.
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, location 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.
Note
: The top-to-bottom order of the rows in the annotation data set matches the left-to-right order of the columns in the input data set. This correspondence is required for markers to be matched appropriately.
Both data sets are included in the
Sample Data
folder that comes with JMP Genomics.
For detailed information about the files and data sets used or created by JMP Life Sciences software, see
Files and Data Sets
.
The output generated by this process is summarized in a Tabbed report. Refer to the
Marker-Trait Association
output documentation for detailed descriptions and guides to interpreting your results.