The
Multiple SNP-Trait Association
process tests for
association
between various types of
traits
and numerically coded
genotypes
from multiple
SNPs
at a time using logistic, linear, or survival
regression
models, as well as generalized linear
mixed models
on SNP genotypes themselves or
principal components
used to represent the SNP genotypes. These methods allow adjustments to be made for quantitative
covariates
and
random effects
or for some trait types,
strata variables
. For
binary traits
,
Hotelling's T-squared test
can be performed as well or instead. For
binary
or
continuous traits
, the
Sequence Kernel Association Test (SKAT)
is also an option.
The Annotation Analysis Group Variable in the
Annotation Data Set
identifies the SNPs to be included in the same
model
together, and models are fit and statistics reported for each unique value of this
variable
(typically a gene) within an annotation group (typically a
chromosome
).
P-values
from these tests, with adjustments applied if requested, are plotted along the marker map, using the location of the first SNP in each annotation analysis group.
See the
MIXED
,
GLIMMIX
,
LOGISTIC
, and
PHREG
procedures in the SAS/STAT User's Guide for more information.
Two data sets are needed for this process. The first required data set, the
Input Data Set
, contains all of the marker data. The sample data set used in the following example, the
morocco_snps1exp_rg.sas7bdat
data set, represents the data from a study of gene
expression
variation and SNP associations in southern Morocco (Idaghdour, Czika,
et al
., 2010) that has been recoded to numeric genotypes using the
Recode Genotypes
process.
Note
: The data was modified slightly to preserve anonymity of subjects.
The
morocco_snps1exp_rg.sas7bdat
data set lists genotype data at 4744 SNPs in 193 individuals. Marker data is presented in the one-column format. 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.
The second required 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
morocco_anno_rg.sas7bdat
annotation data set
is used in this example. 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
Multiple SNP-Trait Association
output documentation for detailed descriptions and guides to interpreting your results.