Relatedness Measures
Click on a button corresponding to a genetics relatedness measure process. Refer to the table below for guidance.
|
Process |
Choose this process for... |
|
Creating a matrix containing kinship or covariance coefficients between pairs of related individuals |
|
|
Computing a symmetric matrix of pairwise relatedness measures for rows of an input data set across all SNP loci |
|
|
Clustering a symmetric relationship or estimated kinship matrix to reduce the size of the random effect that accounts for relatedness in the Q-K Mixed Model process |
|
|
Creating a data set containing columns of a matrix square root, calculated by singular value decomposition |
|
|
This process uses a matrix of marker genotypes, for a sample of individuals that may have come from different ancestral populations, to build the matrix F and factorize it in the form of F=PQ (Cabreros and Storey, 2019). Each row of P can be interpreted as the frequency of a single marker in each of the estimated ancestral populations, and each column of Q can be interpreted as the admixture populations for a single individual. |
|
|
Identifying regions of consecutive SNPs that are shared identical by state (IBS) between a set of affected individuals Note: This process requires a tall data set. |
|
|
Creating a symmetric matrix of dissimilarities between specified groups within a study |
See Genetics for other subcategories.