scran
C++ library for basic single-cell RNA-seq analyses
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scran.hpp
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1#ifndef SCRAN_SCRAN_HPP
2#define SCRAN_SCRAN_HPP
3
4#include "utils/macros.hpp"
5
8
11
13#if __has_include("igraph.h")
15#endif
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41
45
55namespace scran {}
56
57#endif
Aggregate expression values across cells.
Build a shared nearest-neighbor graph on the cells.
Center size factors prior to normalization.
Choose highly variable genes for downstream analyses.
Choose a suitable pseudo-count.
Identify clusters of cells from a shared nearest-neighbor graph.
Downsample a dataset based on its neighbors.
Filter out low-quality cells from the count matrix.
Fit a mean-variance trend to log-count data.
Compute size factors for groups of cells.
Compute hypergeometric tail probabilities.
Compute log-normalized expression values.
Compute median-based size factors.
Model the per-gene variance from log-count data.
Compute PCA after adjusting for differences between batch sizes.
Compute per-cell quality control metrics from an ADT count matrix.
Compute per-cell quality control metrics from a CRISPR guide count matrix.
Compute typical per-cell quality control metrics from an RNA count matrix.
Compute PCA after regressing out an uninteresting factor.
Compute per-cell scores for a feature set.
Compute marker scores for each gene in each group of cells.
Perform a simple PCA on a gene-by-cell matrix.
Create filters to identify low-quality cells from ADT-derived QC metrics.
Create filters to identify low-quality cells from CRISPR-derived QC metrics.
Create filters to identify low-quality cells from RNA-derived QC metrics.
Average parallel elements across vectors.
Set common macros used through libscran.
Functions for single-cell RNA-seq analyses.
Definition AggregateAcrossCells.hpp:18
Quickly compute grouped size factors.
Subset a vector easily.
Create a vector of pointers from a vector of vectors.