Biocview "Transcriptomics"

A CAusal Reasoning tool for Network Identification (from gene expression data) using Integer VALue programming
A CAusal Reasoning tool for Network Identification (from gene expression data) using Integer VALue programming
A CAusal Reasoning tool for Network Identification (from gene expression data) using Integer VALue programming
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
Adaptive Dropout Imputer (ADImpute)
Adaptive Dropout Imputer (ADImpute)
Adaptive Dropout Imputer (ADImpute)
A dimensionality reduction tool using gene detection pattern to mitigate noisy expression profile of scRNA-seq
A dimensionality reduction tool using gene detection pattern to mitigate noisy expression profile of scRNA-seq
A dimensionality reduction tool using gene detection pattern to mitigate noisy expression profile of scRNA-seq
An alignment and integration method for single cell genomics
An alignment and integration method for single cell genomics
Analysis of Cap Analysis of Gene Expression (CAGE) data using Bioconductor
Analysis of Cap Analysis of Gene Expression (CAGE) data using Bioconductor
Analysis Of Differential Abundance Taking Sample and Scale Variation Into Account
Analysis Of Differential Abundance Taking Sample Variation Into Account
Analysis of Transposable Elements
Analyze Transcription Factor Enrichment
Analyze Transcription Factor Enrichment
An R package for the analysis and result reporting of RNA-Seq data by combining multiple statistical algorithms
An R package for the analysis and result reporting of RNA-Seq data by combining multiple statistical algorithms
An R package for the analysis and result reporting of RNA-Seq data by combining multiple statistical algorithms
An R package for the easy provision of simple but complete tab-delimited genomic annotation from a variety of sources and organisms
A search tool for single cell RNA-seq data by gene lists
A search tool for single cell RNA-seq data by gene lists
askoR - Differential Expresion Analysis using edgeR
Assessment of evidence for LOH in spatial transcriptomics pre-processed data using Bayes factor calculations
Assigning scRNA-seq to clone-of-origin using copy number from ultra-low-depth scDNA-seq
A Supervised Approach for **P**r**e**dicting **c**ell Cycle Pr**o**gression using scRNA-seq data
A Supervised Approach for Predicting Cell Cycle Progression Using Single-Cell RNA-seq Data
Asymmetric Within-Sample Transformation
A Tidy Transcriptomics introduction to RNA-Seq analyses
A tool for differential expression analysis and DEGs based investigation to complex diseases by bi-clustering analysis
A Tool for Generic Cell Type Enrichment Analysis
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)
Automated functions for comparing various omic data from cbioportal.org
Automated functions for comparing various omic data from cbioportal.org
Automated functions for comparing various omic data from cbioportal.org
Automated, probabilistic assignment of scRNA-seq to cell types
Base NanoString Experiment Class
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)
Brings Seurat to the Tidyverse
Brings Seurat to the Tidyverse
Brings SingleCellExperiment to the Tidyverse
Brings SummarizedExperiment to the Tidyverse
Brings SummarizedExperiment to the Tidyverse
Brings SummarizedExperiment to the Tidyverse
Brings transcriptomics to the tidyverse
Brings transcriptomics to the tidyverse
Brings transcriptomics to the tidyverse
Brings transcriptomics to the tidyverse
Calculate JCC Scores
Cancer Clone Finder
Cancer Clone Finder
Casc
Causal network analysis methods
CB2 improves power of cell detection in droplet-based single-cell RNA sequencing data
CB2 improves power of cell detection in droplet-based single-cell RNA sequencing data
ccImpute: an accurate and scalable consensus clustering based approach to impute dropout events in the single-cell RNA-seq data
ccImpute: an accurate and scalable consensus clustering based approach to impute dropout events in the single-cell RNA-seq data (https://doi.org/10.1186/s12859-022-04814-8)
Cell-Cycle using Mixture Models
CellRanger Input/Output
Classify Samples From RNA-Seq Datasets
Client for the Reactome Analysis Service for comparative multi-omics gene set analysis
Client for the Reactome Analysis Service for comparative multi-omics gene set analysis
Clone Identification from Single Cell Data
Clone Identification from Single Cell Data
Clone Identification from Single Cell Data
Cluster analysis of Spatial Transcriptomics data
Cluster analysis of Spatial Transcriptomics data
Clustering Algorithms for Bioconductor
Clustering Algorithms for Bioconductor
Clustering and Resolution Enhancement of Spatial Transcriptomes
Clustering and Resolution Enhancement of Spatial Transcriptomes
Co-expression Modules identification Tool
Co-expression Modules identification Tool
COexpression Tables ANalysis
COexpression Tables ANalysis
Comparative Evaluation and Visualization of Differential Expression Analyses
Compare Patient Samples to Cell Line Models Using Molecular Data and Weighted Similarity
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
Context-Aware Transcript Quantification from Long Read RNA-Seq 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
Core Engine for NxtIRF: a User-Friendly Intron Retention and Alternative Splicing Analysis using the IRFinder Engine
COSMOS (Causal Oriented Search of Multi-Omic Space)
COSMOS (Causal Oriented Search of Multi-Omic Space)
Covariate Assisted Large-scale Multiple testing
Covariate Assisted Large-scale Multiple testing
Cross omic genetic fingerprinting
Cross omic genetic fingerprinting
Data-driven Annotation of the Transcriptome
Data normalization by matrix raking
Data structures, clustering and testing for single cell immune receptor repertoires (scRNAseq RepSeq/AIRR-seq)
Decomposing Heterogeneous Cohorts using Omic Data Profiling
Decomposing Heterogeneous Cohorts using Omic Data Profiling
Deconvolution of Expression for Nascent RNA Sequencing Data
Deconvolution of Expression for Nascent RNA Sequencing Data
Deconvolution of mixed cells from spatial and/or bulk gene expression data
Deconvolution of mixed cells from spatial and/or bulk gene expression data
Delineate outstanding genomic zones of differential gene activity
Delineate outstanding genomic zones of differential gene activity
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
Detecting abberant splicing events from RNA-sequencing data
Detecting abberant splicing events from RNA-sequencing data
Determination of essential phenotypic elements of clusters in high-dimensional entities
Determination of essential phenotypic elements of clusters in high-dimensional entities
Differential Alternative Polyadenylation Analysis From Compositions
Differential Expression Analysis for RNA-seq data through a robust variance component test
Differential Gene Expression Analysis for Multi-subject scRNA-seq
Differential Gene Expression Analysis for Multi-subject scRNA-seq
Differentially Expressed Gene-Gene pairs
Differential Topology, Progression and Differentiation
Diffusion scores on biological networks
Diffusion scores on biological networks
Diffusion scores on biological networks
Discriminant Analysis for Evolutionary Inference
Discriminant Analysis for Evolutionary Inference
Empirical Analysis of Digital Gene Expression Data in R
Empirical Analysis of Digital Gene Expression Data in R
Empirical Analysis of Digital Gene Expression Data in R
Enjoy Analyzing And Integrating The Results From Differential Expression Analysis And Functional Enrichment Analysis
Enjoy Analyzing And Integrating The Results From Differential Expression Analysis And Functional Enrichment Analysis
Estimate Promoter Activity from RNA-Seq data
Estimate Promoter Activity from RNA-Seq data
Estimates Isoform Specific RPF Footprint Densities
Evaluate Cellspecific Mixing
Evaluate Cellspecific Mixing
Exon-Intron Split Analysis (EISA) in R
Exon-Intron Split Analysis (EISA) in R
explore metrics for sample annotation for genomic experiments
explore metrics for sample annotation for genomic experiments
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
FCBF-based Co-Expression Networks for Single Cells
FCBF-based Co-Expression Networks for Single Cells
FCBF-based Co-Expression Networks for Single Cells
Filtering of Lowly Expressed Features
Fit Penalised Generalised Least Squares models
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 changes in three biological conditions
Gene expression changes in three biological conditions
Gene Expression Meta-analysis Visualization Tool
Gene Expression Meta-analysis Visualization Tool
Gene Expression Variation Analysis (GEVA)
Gene Expression Variation Analysis (GEVA)
Gene regulator enrichment analysis
Gene regulator enrichment analysis
Gene set analysis accounting for gene-gene correlations
Gene set analysis following differential expression using linear (mixed) modeling with dream
Genetic inteRaction and EssenTiality neTwork mApper
GEOexplorer: a webserver for gene expression analysis and visualisation
GEOexplorer: a webserver for gene expression analysis and visualisation
GEOexplorer: a webserver for gene expression analysis and visualisation
Global Test for Counts
Global Test for Counts
GRaNIE: Reconstruction cell type specific gene regulatory networks including enhancers using chromatin accessibility and RNA-seq data
Graphical Interface for Alternative Splicing Quantification, Analysis and Visualisation
Graphical Interface for Alternative Splicing Quantification, Analysis and Visualisation
Graphical User Interface for High Performance BAM-based binary alternative splicing event quantitation, differential analysis, and visualisation
Helper Functions for LIBD Deconvolution
Helper Functions for LIBD Deconvolution
Higher-Order Deconvolution Survival Analyses
Identification of candidate causal perturbations from differential gene expression data
Identification of candidate causal perturbations from differential gene expression data
Identifies differentially expressed genes with respect to other local genes
Identify, Annotate and Visualize Alternative Splicing and Isoform Switches with Functional Consequences from both short- and long-read RNA-seq data.
Identify, Annotate and Visualize Isoform Switches with Functional Consequences from both short- and long-read RNA-seq data
Identify Different Architectures of Sequence Elements
Identify Different Architectures of Sequence Elements
Identify genes associated with multiple expression phenotypes in single-cell CRISPR screening data
Identify genes associated with multiple expression phenotypes in single-cell CRISPR screening data
ILoReg: a tool for high-resolution cell population identification from scRNA-Seq data
ILoReg: a tool for high-resolution cell population identification from scRNA-Seq data
ILoReg: a tool for high-resolution cell population identification from scRNA-Seq data
Import and summarize transcript-level estimates for transcript- and gene-level analysis
Import and summarize transcript-level estimates for transcript- and gene-level analysis
Improving replicability in single-cell RNA-Seq cell type discovery
Improving replicability in single-cell RNA-Seq cell type discovery
Infer Copy Number Variation from Single-Cell RNA-Seq Data
Infer Copy Number Variation from Single-Cell RNA-Seq Data
Infer Copy Number Variation from Single-Cell RNA-Seq Data
Inference of gene regulatory networks from gene expression data
Infer Ligand-Receptor Interactions from bulk expression (transcriptomics/proteomics) data, or spatial transcriptomics
Inferring the Tree of Cells
Infers biological signatures from gene expression data
In-Silico Annotation of Doublets for Single Cell RNA Sequencing Data
In-Silico Annotation of Doublets for Single Cell RNA Sequencing Data
Integrating Cap Enrichment with Transcript Expression Analysis
Integrating Cap Enrichment with Transcript Expression Analysis
Integrating SpatialExperiment with Simple Features in sf
Integrative Pathway Analysis with Modern PCA Methodology and Gene Selection
Integrative Pathway Analysis with Modern PCA Methodology and Gene Selection
interactive analysis and visualization of alternative splicing in R
Interactive SummarizedExperiment Explorer
Interactive SummarizedExperiment Explorer
Interactive SummarizedExperiment Explorer
Interactive SummarizedExperiment Explorer
Interactive visualization of scRNA-seq data with Cerebro
InterCellar: an R-Shiny app for interactive analysis and exploration of cell-cell communication in single-cell transcriptomics
Interpretable marker-based single-cell pseudotime using Bayesian parametric models
Interpretable marker-based single-cell pseudotime using Bayesian parametric models
Interpretation of RNA-seq experiments through robust, efficient comparison to public databases
Interpretation of RNA-seq experiments through robust, efficient comparison to public databases
Interspecies gene mapping
Introduction to Tidy Transcriptomics
Introduction to Tidy Transcriptomics
Introduction to Tidy Transcriptomics
Introduction to Tidy Transcriptomics
Introduction to Tidy Transcriptomics
Introduction to Tidy Transcriptomics
Introduction to Tidy Transcriptomics
Introduction to Tidy Transcriptomics
iSEE Universe
iSEE Universe
iSEE Universe
iSMNN: Batch Effect Correction for Single-cell RNA-seq data via Iterative Supervised Mutual Nearest Neighbor Refinement
KnowSeq R/Bioc package: The Smart Transcriptomic Pipeline
KnowSeq R/Bioc package: The Smart Transcriptomic Pipeline
Landscape Single Cell Entropy
Learn and Apply Cell Type Signatures
Learn and Apply Cell Type Signatures
Linear Models for Microarray Data
Linear Models for Microarray Data
Log Fold Change Distribution Tools for Working with Ratios of Counts
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
Mean Alterations Using Discrete Expression
megadepth: BigWig and BAM related utilities
megadepth: BigWig and BAM related utilities
Methods for analyzing spatially resolved transcriptomics data
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
Mini-batch K-means Clustering for Single-Cell RNA-seq
Mini-batch K-means Clustering for Single-Cell RNA-seq
Minimized Single-Cell Consensus Clustering
Minimized Single-Cell Consensus Clustering
MLG Clustering
Model-based Analysis of Single Cell Transcriptomics
Model-based Analysis of Single Cell Transcriptomics
MOGAMUN: A Multi-Objective Genetic Algorithm to Find Active Modules in Multiplex Biological Networks
MOGAMUN: A Multi-Objective Genetic Algorithm to Find Active Modules in Multiplex Biological Networks
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
Multi-Contrast Gene Set Enrichment Analysis
Multi-Contrast Gene Set Enrichment Analysis
Multi-Contrast Gene Set Enrichment Analysis
Multi Omic Master Regulator Analysis
Multi Omic Master Regulator Analysis
Multivariate analysis of microarray data using ADE4
NanoString data normalization and differential gene expression analysis
NanoString GeoMx Tools
NanoString nCounter Tools
Negative binomial model for scRNA-seq
Negative binomial model for scRNA-seq
Network Analysis Supported by Boosting
Network Perturbation Amplitude
Network Perturbation Amplitude
Network smoothing for scRNAseq
Network smoothing for scRNAseq
NEUral network-based single-Cell Annotation tool
Normalization of Single-Cell mRNA Sequencing Data
Object design (S4) for AMARETTO
Omics Longitudinal Differential Analysis
Omics Longitudinal Differential Analysis
OmniPath web service client and more
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
Optimising the Definition of Expressed Regions
Outlier Analysis for pairwise differential comparison
Outlier Analysis for pairwise differential comparison
Outlier Analysis for pairwise differential comparison
Outlier-aware and Count-based Compositional Analysis of Single-cell Data.
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
Perform co-DE gene analysis
Phenotypic EMD for comparison of single-cell samples
Phenotypic EMD for comparison of single-cell samples
Phenotypic EMD for comparison of single-cell samples
pipeComp pipeline benchmarking framework
pipeComp pipeline benchmarking framework
Pipeline for augmented co-expression analysis
Pipeline for augmented co-expression analysis
Pipelines for Bi-Clustering Using Matrix Factorization
Plots and annotation for choosing BrainFlow target probe sequence
Plots and annotation for choosing BrainFlow target probe sequence
PolyA counting and differential transcript usage analysis for scRNA-seq data
Pretrained learning models for cell type prediction on single cell RNA-sequencing data
Pretrained learning models for cell type prediction on single cell RNA-sequencing data
Probabilistic Outlier Identification for RNA Sequencing Generalized Linear Models
Probabilistic Outlier Identification for RNA Sequencing Generalized Linear Models
Programmatic access to the DEE2 RNA expression dataset
Programmatic access to the DEE2 RNA expression dataset
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 of Normalized Gene Expression Data
Quantification of the Tumor Immune contexture from RNA-seq data
Quantify and interpret divers of variation in multilevel gene expression experiments
Quantify and interpret drivers of variation in multilevel gene expression experiments
Rank-based signature enrichment analysis for single-cell data
RcisTarget: Identify transcription factor binding motifs enriched on a gene list
RcisTarget Identify transcription factor binding motifs enriched on a list of genes or genomic regions
Reference-Based Single-Cell RNA-Seq Annotation
Reference-Based Single-Cell RNA-Seq Annotation
Reference-free Cell-Type Deconvolution of Multi-Cellular Spatially Resolved Transcriptomics Data
Reference-guided isoform reconstruction and quantification for long read RNA-Seq data
Regulation Simulator of Interaction between miRNA and Competing RNAs (ceRNA)
Regulation Simulator of Interaction between miRNA and Competing RNAs (ceRNA)
Retrieves Condition-Specific Variants in RNA-Seq Data
Retrieves Condition-Specific Variants in RNA-Seq Data
RiboseQC, a Comprehensive Ribo-Seq Analysis Tool
'rifi' analyses data from rifampicin time series created by microarray or RNAseq
RLSeq: An analysis package for R-loop mapping data
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 wrapper for SpatialDE
S4 Class for Spatially Resolved -omics Data
S4 Class for Spatially Resolved -omics Data
SAFE-clustering:Single-cell Aggregated (From Ensemble) Clustering for Single-cell RNA-seq Data
SAME: Single-cell RNA-seq Aggregated clustering via Mixture model Ensemble for Single-cell RNA-seq Data
Scalable Analysis of Differential Transcript Usage for Bulk and Single-Cell RNA-sequencing Applications
Scalable Analysis of Differential Transcript Usage for Bulk and Single-Cell RNA-sequencing Applications
Scalable differential expression analysis of single cell transcriptomics datasets with complex study designs
Scalable identification of spatially variable genes in spatially-resolved transcriptomics data
Scaling normalization based on the Pareto distribution
SCANVIS - a tool for SCoring, ANnotating and VISualizing splice junctions
SCANVIS - a tool for SCoring, ANnotating and VISualizing splice junctions
scFeatures: Multi-view representations of single-cell and spatial data for disease outcome prediction
scMerge: Merging multiple batches of scRNA-seq data
scMerge: Merging multiple batches of scRNA-seq data
scReClassify: post hoc cell type classification of single-cell RNA-seq data
scRecover for imputation of single-cell RNA-seq data
scRecover for imputation of single-cell RNA-seq data
scRecover for imputation of single-cell RNA-seq data
Selecting transcript model using PRO-seq
Shiny-based interactive data-quality exploration for omics data
Signature-based Clustering for Diagnostic Purposes
Signature-based Clustering for Diagnostic Purposes
Signature-based Clustering for Diagnostic Purposes
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
Simulation and Deconvolution of Omic Profiles
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 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 Batch Correction Methods
Single-Cell Consensus Clustering
Single-Cell Consensus Clustering
Single Cell Entropy
single-cell higher order testing
single-cell higher order testing
Single Cell Overview of Normalized Expression data
Single Cell Overview of Normalized Expression data
Single cell replicability analysis
Single cell replicability analysis
Single-Cell RNA-Seq Analysis Utilities
Single-Cell RNA-Seq Analysis Utilities
Single Cell Shiny Application for Analysing Single Cell Transcriptomics Data
Single-cell Targetted Network Inference
Single-Cell UTR Bootstrap Tools
Small-Count Analysis Methods for High-Dimensional Data
Small-Count Analysis Methods for High-Dimensional Data
SMNN: Batch Effect Correction for Single-cell RNA-seq data with Supervised Mutual Nearest Neighbor Detection
Sparse Partial Correlations On Gene Expression
Sparse Partial Correlations On Gene Expression
Sparse Partial Correlations On Gene Expression
Spatial Overlay for Omic Data from Nanostring GeoMx Data
Spatial Reconstruction of Tissues from scRNA-seq Data
Spatial transcriptome analyses of Nanostring's DSP data in R
Spatial Transcriptomics Analysis
Spatial Transcriptomics Analysis
Splicing Diversity Analysis for Transcriptome Data
Splicing Diversity Analysis for Transcriptome Data
SpotClean adjusts for spot swapping in spatial transcriptomics data
ssPATHS: Single Sample PATHway Score
ssPATHS: Single Sample PATHway Score
ssPATHS: Single Sample PATHway Score
Standardize Antibody Names
Stan implementation of BASiCS
stJoincount - Join count statistic for quantifying spatial correlation between clusters
Structure Learning for Count Data
Suffix Array Kernel Smoothing for discovery of correlative sequence motifs and multi-motif domains
Switch-like differential expression across single-cell trajectories
Switch-like differential expression across single-cell trajectories
text mining for msigdb sets construed as documents
TFutils
TFutils
TFutils
the R package for analyzing expression evolution based on RNA-seq data
The scigenex package (Single-Cell Informative GENe Explorer)
The scigenex package (Single-Cell Informative GENe Explorer)
The tidyomics blog
The tidyomics blog
Tidy Meta Profiles using Bioconductor and the Tidyverse
Tidy Transcriptomics for Single-cell RNA Sequencing Analyses
Tidyverse functions for SummarizedExperiment
Tomo-seq data analysis
Tomo-seq data analysis
Tools for finding Total RNA Expression Genes in single nucleus RNA-seq data
Tools for matrices with precision weights, test and explore weighted or sparse data
Tools for matrices with precision weights, test and explore weighted or sparse data
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
Tools to work with a Compendium of 181000 human transcriptome sequencing studies
Tools to work with a Compendium of 181000 human transcriptome sequencing studies
Top Confident Effect Sizes
Top Confident Effect Sizes
trajectory-based differential expression analysis for sequencing data
trajectory-based differential expression analysis for sequencing data
Trajectory functions for visualization and interpretation.
Transcriptional Data Guided fMRI Network Classification
Transcriptome CUTteR
Transcript Quantification Import with Automatic Metadata
Transcript Quantification Import with Automatic Metadata
Translational control assessment from ribosome footprint and total RNA libraries
tricycle: Transferable Representation and Inference of cell cycle
TSS sequencing data analysis
Unified statistal Modeling of Omics Data
Unified statistal Modeling of Omics Data
Unlocking iSEE for transcript-level visualization
User Friendly Single-Cell and Bulk RNA Sequencing Visualization
User Friendly Single-Cell and Bulk RNA Sequencing Visualization
User Friendly Single-Cell and Bulk RNA Sequencing Visualization
Utilities for Handling Single-Cell Droplet Data
Utilities for Handling Single-Cell Droplet Data
Varying-Censoring Aware Matrix Factorization
VeloViz: RNA-velocity informed 2D embeddings for visualizing cell state trajectories
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
Visualization functions for spatial transcriptomics data
Weighting protein-protein interactions
What the Package Does TODOELI
Zero-Inflated Negative Binomial Model for RNA-Seq Data
Zero-Inflated Negative Binomial Model for RNA-Seq Data