scran_pca
Principal component analysis for single-cell data
Loading...
Searching...
No Matches
Classes | Namespaces | Functions
blocked_pca.hpp File Reference

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)
 

Detailed Description

Perform PCA on residuals after regressing out a blocking factor.