Documentation
Principal Components AnalysisDescription
DISSECT can conduct principal component analysis. This type of analysis could be very computational demanding for high number of individuals and high number of markers. DISSECT parallelization opens the door to analyze huge datasets. Principal components analysis is performed by GRM diagonalization.
Examples
Perform a PCA analysis using genotypes in genotypes file.
dissect --pca --bfile genotypes --out results
Perform a PCA analysis using a precomputed GRM.
dissect --pca --grm grmfile --out results
Options
Analysis Options
--pca |
Perform PCA analysis |
Input Options
--bfile f |
Specify a genotypes file. |
--bfile-list f |
Specify a file with a list of genotypes files. |
--grm f |
Specify the GRM file. |
Output Options
--out f |
Specify the base name for output files. |
Others
--num-eval n |
Specify the number of eigenvectors/eigenvalues that will be stored. |
Output description
Two files are generated after a PCA analysis. A file with the eigenvectors and a file with the eigenvalues.
Eigenvalues file
file extension: .pca.eigenvalues
This file contains the first bigger estimated eigenvalues. The number of eigenvalues depends on –num-eval option.
Eigenvectors file
file extension: .pca.eigenvectors
The first two columns contain the individual family ID and individual ID, respectively. The following columns contain the eigenvectors. Each column contain an eigenvector for each eigenvalue in eigenvalues file. The number of eigenvectors depends on –num-eval option.