Processes | Genetics | QTL Single Marker Analysis

QTL Single Marker Analysis
The QTL Single Marker Analysis process provides you with a way to quickly scan the whole genome for evidence of QTL signals. It performs a simple regression for each marker with trait values and computes the probability of QTL evidence for each marker.
What do I need?
Two SAS data sets are required. The first, the input cross file, lists information about the different genetic crosses used in the study. The qtlbcsample_geno.sas7bdat data set, used in the following example, is shown below. This is a wide data set with 300 individuals listed in rows, and the status of individuals for two traits and 36 markers, spanning 3 chromosomes , listed in columns. Markers are formatted as numeric genotypes .
The second required data set is an Annotation Data Set , that lists map information for each of the markers. The qtlbcsample_anno.sas7bdat annotation data set , used in the following example, is shown below. This data set contains 4 columns listing the name and position (in cM) of 36 QTL markers present on three chromosomes.
Both the qtlbcsample_geno.sas7bdat and the qtlbcsample_anno.sas7bdat data sets are located in the Sample Data\QtlMapping directory included 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 QTL Single Marker Analysis output documentation for detailed descriptions and guides to interpreting your results.
More detailed analyses, such as Interval Mapping or Multiple-Interval Mapping, can be done to further delimit the region of significance.