Skip to main content Module eigensnp Copy item path Source CondensedFeatureId Identifies a row (a condensed feature) in the condensed feature matrix. EigenSNPCoreAlgorithm Orchestrates the EigenSNP PCA algorithm.
Holds the configuration and provides the main execution method. EigenSNPCoreAlgorithmConfig Configuration for the core EigenSNP PCA algorithm’s internal parameters.
These parameters define the behavior of various algorithmic stages. EigenSNPCoreOutput Encapsulates the final results of the EigenSNP PCA computation. InitialSamplePcScores Represents the initial Principal Component scores for all N samples,
derived from the PCA on the StandardizedCondensedFeatures. LdBlockListId Identifies an LD Block from the input list of LdBlockSpecifications. LdBlockSpecification Specification for a single Linkage Disequilibrium (LD) block. PcaSnpId Identifies a SNP included in the PCA (post-QC and part of an LD block).
This index is relative to the final list of SNPs used in the analysis. PcaSnpMetadata Holds the essential metadata for a single SNP used in the PCA.
The order of these structs in a Vec should correspond to the PcaSnpId. PerBlockLocalSnpBasis Represents the learned local eigenSNP basis vectors for a single LD block. PrincipalComponentId Identifies one of the K final computed Principal Components. QcSampleId Identifies a sample included in the PCA (post-QC).
This index is relative to the final list of QC’d samples. RawCondensedFeatures Represents the raw condensed feature matrix (A_eigen_star) before row-wise standardization.
Its features (rows) are the projections of all samples onto the local eigenSNP bases. StandardizedCondensedFeatures Represents the condensed feature matrix (A_eigen_std_star) after its features (rows)
have been standardized (mean-centered and scaled to unit variance). PcaReadyGenotypeAccessor Defines how the EigenSNP PCA algorithm accesses globally standardized genotype data.
The implementor of this trait is responsible for handling the actual data source
and applying pre-calculated global mean (mu_j) and
standard deviation (sigma_j) for each SNP j to provide X_ji = (G_qc,ji - mu_j) / sigma_j. reorder_array_owned Reorders the elements of a 1D array (Array1) based on a given slice of indices.
Returns a new owned Array1<T> with elements in the specified order. reorder_columns_owned Reorders the columns of a 2D array (Array2) based on a given slice of indices.
Returns a new owned Array2<T> with columns in the specified order. LocalBasisWithDiagnostics PcaConditionally PcaOutputWithDiagnostics ThreadSafeStdError A thread-safe wrapper for standard dynamic errors,
so they implement Send and Sync.