scran_pca
Principal component analysis for single-cell data
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Perform PCA on residuals after regressing out a blocking factor. More...
#include "tatami/tatami.hpp"
#include "irlba/irlba.hpp"
#include "irlba/parallel.hpp"
#include "Eigen/Dense"
#include <vector>
#include <cmath>
#include <algorithm>
#include <type_traits>
#include "scran_blocks/scran_blocks.hpp"
#include "utils.hpp"
Go to the source code of this file.
Classes | |
struct | scran_pca::BlockedPcaOptions |
Options for blocked_pca() . More... | |
struct | scran_pca::BlockedPcaResults< EigenMatrix_, EigenVector_ > |
Results of blocked_pca() . More... | |
Namespaces | |
namespace | scran_pca |
Principal component analysis on single-cell data. | |
Functions | |
template<typename Value_ , typename Index_ , typename Block_ , typename EigenMatrix_ , class EigenVector_ > | |
void | scran_pca::blocked_pca (const tatami::Matrix< Value_, Index_ > &mat, const Block_ *block, const BlockedPcaOptions &options, BlockedPcaResults< EigenMatrix_, EigenVector_ > &output) |
template<typename EigenMatrix_ = Eigen::MatrixXd, class EigenVector_ = Eigen::VectorXd, typename Value_ , typename Index_ , typename Block_ > | |
BlockedPcaResults< EigenMatrix_, EigenVector_ > | scran_pca::blocked_pca (const tatami::Matrix< Value_, Index_ > &mat, const Block_ *block, const BlockedPcaOptions &options) |
Perform PCA on residuals after regressing out a blocking factor.