Biocview "SingleCell"

Access matrix-like HDF5 server content or BigQuery content through a SummarizedExperiment interface
Access matrix-like HDF5 server content or BigQuery content through a SummarizedExperiment interface
Access matrix-like HDF5 server content or BigQuery content through a SummarizedExperiment interface
A correlation-based method for quality filtering of single-cell RNAseq data
AIPS : Absolute Inference of Patient Signatures
Analysis of Copy Number Variation in Single-Cell-Sequencing Data
Analysis of Copy Number Variation in Single-Cell-Sequencing Data
Analysis of RNA-Seq Count Data by Using Multiple Corespondence Analysis
Analysis of RNA-Seq Count Data by Using Multiple Corespondence Analysis
Analysis of RNA-Seq Count Data using Multiple Corespondence Analysis
An implementation of clustering and subpopulation relationship analysis (scGPS = single cell Global Predictions of Subpopulation)
An R interface for computational modeling of tumor progression
An R interface for computational modeling of tumor progression
A package to extract spatial features based on multiplex IF images
A package to extract spatial features based on multiplex IF images
A package to extract spatial features based on multiplex IF images
ascend - Analysis of Single Cell Expression, Normalisation, and Differential expression
A search tool for single cell RNA-seq data by gene lists
A search tool for single cell RNA-seq data by gene lists
Assigning scRNA-seq to clone-of-origin using copy number from ultra-low-depth scDNA-seq
A tool for unsupervised projection of single cell RNA-seq data
A tool for unsupervised projection of single cell RNA-seq data
A tool for unsupervised projection of single cell RNA-seq data
A toolkit for performing KNN-based statistics for flow and mass cytometry data
A toolkit for performing KNN-based statistics for flow and mass cytometry data
AUCell: Analysis of 'gene set' activity in single-cell RNA-seq data (e.g. identify cells with specific gene signatures)
AUCell: Analysis of 'gene set' activity in single-cell RNA-seq data (e.g. identify cells with specific gene signatures)
Augmented functionality for analysis of epigenomic variance
Bayesian Analysis of Single-Cell Sequencing data
Bayesian Analysis of Single-Cell Sequencing data
Bayesian hierarchical mixture of factor analyzers for modelling genomic bifurcations
Bayesian hierarchical mixture of factor analyzers for modelling genomic bifurcations
BEARscc (Bayesian ERCC Assesstment of Robustness of Single Cell Clusters)
BEARscc (Bayesian ERCC Assesstment of Robustness of Single Cell Clusters)
Cancer Clone Finder
Cancer Clone Finder
Chromatin Variation Across Regions
Chromatin Variation Across Regions
Clone and Donor Identification from Single Cell Data
Clone and Donor Identification from Single Cell Data
Compare Characteristic Features of Count Data Sets
Compare Clusterings for Single-Cell Sequencing
Compare Clusterings for Single-Cell Sequencing
Compare Clusterings for Single-Cell Sequencing
Compare Clusterings for Single-Cell Sequencing
Compute cell-type specific enrichments with high resolution
Condition Comparison in scRNA-seq Data
Cytometry dATa anALYSis Tools
Cytometry dATa anALYSis Tools
Cytometry dATa anALYSis Tools
Deconvolution of Bulk Sequencing Experiments using Single Cell Data
DEsingle for detecting three types of differential expression in single-cell RNA-seq data
DEsingle for detecting three types of differential expression in single-cell RNA-seq data
Differential discovery in high-dimensional cytometry via high-resolution clustering
Differential discovery in high-dimensional cytometry via high-resolution clustering
Differential expression analysis and model fitting for single-cell RNA-seq data
Differential expression analysis and model fitting for single-cell RNA-seq data
exploratory data analysis of tabula muris droplet counts
Factorial Latent Variable Modeling of Single-Cell RNA-Seq Data
Factorial Latent Variable Modeling of Single-Cell RNA-Seq Data
Factorial Latent Variable Modeling of Single-Cell RNA-Seq Data
Find breakpoints in Strand-seq data
Find breakpoints in Strand-seq data
Functional interpretation of single cell RNA-seq latent manifolds
Functional interpretation of single cell RNA-seq latent manifolds
Functions to conduct quality control analysis in methylation data
Functions to conduct quality control analysis in methylation data
GenoMetric Query Language for R/Bioconductor
GenoMetric Query Language for R/Bioconductor
Genomic trajectories with heterogeneous genetic and environmental backgrounds
HDF5 backend for DelayedArray objects
Inference of Chromosome-length Haplotypes using Genomic Data of Single Gamete Cells
Inference of Chromosome-Length Haplotypes Using Genomic Data of Single Gamete Cells
Interactive Analysis of Single Cell RNA-Seq Data
Interactive Analysis of Single Cell RNA-Seq Data
Interactive SummarizedExperiment Explorer
Interactive SummarizedExperiment Explorer
Interactive SummarizedExperiment Explorer
Interpretable marker-based single-cell pseudotime using Bayesian parametric models
Interpretable marker-based single-cell pseudotime using Bayesian parametric models
Linear model and normality based transformation method (Linnorm)
Linear model and normality based transformation method (Linnorm)
LoomExperiment container
Merging of phenotype information from different cytometric profiles
Methods for Single-Cell RNA-Seq Data Analysis
Methods for Single-Cell RNA-Seq Data Analysis
Methods for Single-Cell RNA-Seq Data Analysis
Mine Associated Gene Expressions (from single-cell Rna Seq data)
Mixture modeling of single-cell RNA-seq data to identify genes with differential distributions
Mixture modeling of single-cell RNA-seq data to identify genes with differential distributions
Mixture modeling of single-cell RNA-seq data to indentify genes with differential distributions
Mixture Nested Effects Models
Model-based Analysis of Single Cell Transcriptomics
Model-based Analysis of Single Cell Transcriptomics
Model-based Analysis of Single Cell Transcriptomics
Model higher-order methylation profiles
Model higher-order methylation profiles
Model higher-order methylation profiles
Network smoothing for scRNAseq
Network smoothing for scRNAseq
Normalization of single cell RNA-seq data
Normalization of single cell RNA-seq data
Normalization of single cell RNA-seq data
ontological exploration of scRNA-seq of 1.3 million mouse neurons from 10x genomics
ontological exploration of scRNA-seq of 1.3 million mouse neurons from 10x genomics
pipeline for single cell RNA-seq data analysis
pipeline for single cell RNA-seq data analysis
Reconstruction, visualization and analysis of branching trajectories
Reconstruction, visualization and analysis of branching trajectories
S4 Classes for Single Cell Data
S4 Classes for Single Cell Data
S4 Classes for Single Cell Data
S4 Classes for Single Cell Data
SAFE-clustering:Single-cell Aggregated (From Ensemble) Clustering for Single-cell RNA-seq Data
SCENIC (Single Cell rEgulatory Network Inference and Clustering)
SIMLR: Single-cell Interpretation via Multi-kernel LeaRning
Simple Simulation of Single-cell RNA Sequencing Data
Simple Simulation of Single-cell RNA Sequencing Data
Simple Simulation of Single-cell RNA Sequencing Data
Single-cell analysis toolkit for gene expression data in R
Single-Cell Analysis Toolkit for Gene Expression Data in R
Single-Cell Analysis Toolkit for Gene Expression Data in R
Single-Cell Clustering Visualization
Single-Cell Consensus Clustering
Single-Cell Consensus Clustering
Single-Cell Consensus Clustering
Single Cell Overview of Normalized Expression data
Single Cell Overview of Normalized Expression data
Single Cell Overview of Normalized Expression data
Single cell replicability analysis
Single cell replicability analysis
Single-cell RNAseq cell cluster labelling by reference
Single-cell RNA sequencing data normalization
Single Cell RNA-Seq UMI Filtering Facilitator (scruff)
Single Cell RNA-Seq UMI Filtering Facilitator (scruff)
Single Cell RNA-Seq UMI Filtering Facilitator (scruff)
Single Cell RNA-Seq UMI Filtering Facilitator (scruff)
Single-Cell RNA-Seq Utilities
Single-Cell RNA-Seq Utilities
Single-Cell RNA-Seq Utilities
Statistical Inferences with MeDIP-seq Data (SIMD) to infer the methylation level for each CpG site
Switch-like differential expression across single-cell trajectories
Switch-like differential expression across single-cell trajectories
Title: SIMLR and CIMLR Multi-kernel LeaRning methods
Title: SIMLR: Single-cell Interpretation via Multi-kernel LeaRning
Tools for ordering single-cell sequencing
TRONCO, an R package for TRanslational ONCOlogy
TRONCO, an R package for TRanslational ONCOlogy
TRONCO, an R package for TRanslational ONCOlogy
Using Mass Cytometry for Differential Abundance Analyses
Using Mass Cytometry for Differential Abundance Analyses
Using Mass Cytometry for Differential Abundance Analyses
Utilities for Handling Single-Cell Droplet Data
Utilities for Handling Single-Cell Droplet Data
Varying-Censoring Aware Matrix Factorization
Zero-Inflated Negative Binomial Model for RNA-Seq Data
Zero-Inflated Negative Binomial Model for RNA-Seq Data
Zero-Inflated Negative Binomial Model for RNA-Seq Data