scran::ResidualPca::Results Struct Reference

Container for the PCA results. More...

#include <ResidualPca.hpp>

Public Attributes
Eigen::MatrixXd	pcs
Eigen::VectorXd	variance_explained
double	total_variance = 0
Eigen::MatrixXd	rotation
Eigen::MatrixXd	center
Eigen::VectorXd	scale

Detailed Description

Container for the PCA results.

Instances should be constructed by the ResidualPca::run() methods.

Member Data Documentation

pcs

Eigen::MatrixXd scran::ResidualPca::Results::pcs

Matrix of principal components. By default, each row corresponds to a PC while each column corresponds to a cell in the input matrix. If set_transpose() is set to false, rows are cells instead. The number of PCs is determined by set_rank().

variance_explained

Eigen::VectorXd scran::ResidualPca::Results::variance_explained

Variance explained by each PC. Each entry corresponds to a column in pcs and is in decreasing order.

total_variance

double scran::ResidualPca::Results::total_variance = 0

Total variance of the dataset (possibly after scaling, if set_scale() is set to true). This can be used to divide variance_explained to obtain the percentage of variance explained.

rotation

Eigen::MatrixXd scran::ResidualPca::Results::rotation

Rotation matrix, only returned if ResidualPca::set_return_rotation() is true. Each row corresponds to a feature while each column corresponds to a PC. The number of PCs is determined by set_rank(). If feature filtering was performed, the number of rows is equal to the number of features remaining after filtering.

center

Eigen::MatrixXd scran::ResidualPca::Results::center

Centering matrix, only returned if ResidualPca::set_return_center() is true. Each row corresponds to a row in the input matrix and each column corresponds to a block, such that each entry contains the mean for a particular feature in the corresponding block. If feature filtering was performed, the number of rows is equal to the number of features remaining after filtering.

scale

Eigen::VectorXd scran::ResidualPca::Results::scale

Scaling vector, only returned if ResidualPca::set_return_center() is true. Each entry corresponds to a row in the input matrix and contains the scaling factor used to divide the feature values if ResidualPca::set_scale() is true. If feature filtering was performed, the length is equal to the number of features remaining after filtering.

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The documentation for this struct was generated from the following file:

• scran/dimensionality_reduction/ResidualPca.hpp