Biocview "Transcriptomics"

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
Analysis of Cap Analysis of Gene Expression (CAGE) data using Bioconductor
Analysis of Cap Analysis of Gene Expression (CAGE) data using Bioconductor
Analyze Transcription Factor Enrichment
Analyze Transcription Factor Enrichment
An R package to Identify, Annoatate and Visialize Isoform Switches with Functional Consequences (from RNA-seq data)
An R package to Identify, Annotate and Visualize Alternative Splicing and Isoform Switches with Functional Consequences (from RNA-seq data)
An R package to Identify, Annotate and Visualize Alternative Splicing and Isoform Switches with Functional Consequences (from RNA-seq data)
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
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)
Bayesian Analysis of Single-Cell Sequencing data
Bayesian Analysis of Single-Cell Sequencing data
BEARscc (Bayesian ERCC Assesstment of Robustness of Single Cell Clusters)
BEARscc (Bayesian ERCC Assesstment of Robustness of Single Cell Clusters)
Calculate JCC Scores
Cancer Clone Finder
Cancer Clone Finder
Causal network analysis methods
Causal network analysis methods
Cell-Cycle using Mixture Models
Clone and Donor Identification from Single Cell Data
Clone and Donor Identification from Single Cell Data
Cluster analysis of Spatial Transcriptomics data
Co-expression Modules identification Tool
Co-expression Modules identification Tool
Compendium of human transcriptome sequences
Computational pipeline for computing probability of modification from structure probing experiment data
Computational pipeline for computing probability of modification from structure probing experiment data
Computational pipeline for computing probability of modification from structure probing experiment data
Controlling bias and inflation in association studies using the empirical null distribution
Controlling bias and inflation in association studies using the empirical null distribution
Conversion between the Workflow4metabolomics tabulated format and the ExpressionSet bioconductor class
Cross omic genetic fingerprinting
Cross omic genetic fingerprinting
Decomposing Heterogeneous Cohorts using Omic Data Profiling
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
Exposome and omic data associatin and integration analysis
Exposome and omic data associatin and integration analysis
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
Finds Gene Co-expression Modules
Functional interpretation of single cell RNA-seq latent manifolds
Functional interpretation of single cell RNA-seq latent manifolds
Gene expression-based subtype classification for high-grade serous ovarian cancer
Gene expression-based subtype classification for high-grade serous ovarian cancer
Gene expression-based subtype classification for high-grade serous ovarian cancer
Gene expression changes in three biological conditions
Gene expression changes in three biological conditions
Global Test for Counts
Global Test for Counts
Graphical Interface for Alternative Splicing Quantification, Analysis and Visualisation
Graphical Interface for Alternative Splicing Quantification, Analysis and Visualisation
Graphical Interface for Alternative Splicing Quantification, Analysis and Visualisation
Identification of candidate causal perturbations from differential gene expression data
Identification of candidate causal perturbations from differential gene expression data
Imputation for single-cell RNA-seq data
Inferring the Tree of Cells
Infers biological signatures from gene expression data
Infers biological signatures from gene expression data
Integrating Cap Enrichment with Transcript Expression Analysis
Integrating Cap Enrichment with Transcript Expression Analysis
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
Log fold change distribution tools for working with ratios of counts
Log fold change distribution tools for working with ratios of counts
Long gene expression as a metric for neuronal identity
Mapping Alternative Splicing Events to pRoteins
Mapping Alternative Splicing Events to pRoteins
Maximum Likelihood Decay Modeling of RNA Degradation Data
Maximum Likelihood Decay Modeling of RNA Degradation Data
Methods for Single-Cell RNA-Seq Data Analysis
Methods for Single-Cell RNA-Seq Data Analysis
Methods for Single-Cell RNA-Seq Data Analysis
Michaelis-Menten Modelling of Dropouts in single-cell RNASeq
Michaelis-Menten Modelling of Dropouts in single-cell RNASeq
Michaelis-Menten Modelling of Dropouts in single-cell RNASeq
Michaelis-Menten Modelling of Dropouts in single-cell RNASeq
Model-based Analysis of Single Cell Transcriptomics
Model-based Analysis of Single Cell Transcriptomics
Model-based Analysis of Single Cell Transcriptomics
Molecular Degree of Perturbation calculates scores for transcriptome data samples based on their perturbation from controls
Molecular Degree of Perturbation calculates scores for transcriptome data samples based on their perturbation from controls
Molecular Degree of Perturbation calculates scores for transcriptome data samples based on their perturbation from controls
Network smoothing for scRNAseq
Network smoothing for scRNAseq
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
OUTRIDER - OUTlier in RNA-Seq fInDER
OUTRIDER - OUTlier in RNA-Seq fInDER
PCA, PLS(-DA) and OPLS(-DA) for multivariate analysis and feature selection of omics data
PCA, PLS(-DA) and OPLS(-DA) for multivariate analysis and feature selection of omics data
PCA, PLS(-DA) and OPLS(-DA) for multivariate analysis and feature selection of omics data
Phenotypic EMD for comparison of single-cell samples
Quality Control for Single-Cell RNA-seq Data
Quality Control for Single-Cell RNA-seq Data
Quality Control for Single-Cell RNA-seq Data
Quality Control for Single-Cell RNA-seq Data
RcisTarget: Identify transcription factor binding motifs enriched on a gene list
RcisTarget: Identify transcription factor binding motifs enriched on a gene list
Retrieves Condition-Specific Variants in RNA-Seq Data
Retrieves Condition-Specific Variants in RNA-Seq Data
RNA Centric Annotation System
RNA Centric Annotation System
RNA Centric Annotation System
RNA-seq analysis using multiple algorithms
RNA-seq analysis using multiple algorithms
R package for RIVER (RNA-Informed Variant Effect on Regulation)
R package for RIVER (RNA-Informed Variant Effect on Regulation)
R package for RIVER (RNA-Informed Variant Effect on Regulation)
R package for RIVER (RNA-Informed Variant Effect on Regulation)
SAFE-clustering:Single-cell Aggregated (From Ensemble) Clustering for Single-cell RNA-seq Data
Signature-based Clustering for Diagnostic Purposes
Signature-based Clustering for Diagnostic Purposes
Signature discovery from omics data
Signature discovery from omics data
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 Batch Correction Methods
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 Targetted Network Inference
Sparse Partial Correlations On Gene Expression
Sparse Partial Correlations On Gene Expression
Switch-like differential expression across single-cell trajectories
Switch-like differential expression across single-cell trajectories
Switch-like differential expression across single-cell trajectories
Testing for association between RNA-Seq and high-dimensional data
TFutils
TFutils
Tidy Meta Profiles using Bioconductor and the Tidyverse
Tools for ordering single-cell sequencing
Tools for ordering single-cell sequencing
Tools for spliced gene structure manipulation and analysis
Tools for spliced gene structure manipulation and analysis
Transcript Quantification Import with Automatic Metadata
Transcript Quantification Import with Automatic Metadata
Translational control assessment from ribosome footprint and total RNA libraries
Utilities for Handling Single-Cell Droplet Data
Utilities for Handling Single-Cell Droplet Data
Varying-Censoring Aware Matrix Factorization
Visual and interactive gene expression analysis
Visual and interactive gene expression analysis
Visual and interactive gene expression analysis
Visual Exploration of Omic Datasets Using a Shiny App
Visual Exploration of Omic Datasets Using a Shiny App
Visual Exploration of Omic Datasets Using a Shiny App
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