Biocview "Clustering"

A Basic R Package to Demonstrate a Cycle of Code Development

A bioconductor package for high-dimensional exploration of biological network heterogeneity

Accelerated similarity searching of small molecules

Accurate hierarchical clustering for huge data

Accurate Inference of Genetic Ancestry from Cancer Sequencing

A collection of tools for imaging MS data processing

A complete analysis of single cell subpopulations, from identifying subpopulations to analysing their relationship (scGPS = single cell Global Predictions of Subpopulation)

A Comprehensive R Package For Analyzing Quantitative Phosphoproteomics Data

Adjacency-Constrained Clustering of a Block-Diagonal Similarity Matrix

Advanced analysis of microbial flow cytometry data

A fast hierarchical graph-based clustering method

A Fast Scalable and Flexible Non Negative Matrix Factorization Method

Affinity Network Fusion for Complex Patient Clustering

A Framework for Consensus Partitioning

A gene recommender algorithm to identify genes coexpressed with a query set of genes

A Graphical User Interface for accessing and modeling the Cancer Genomics Data of MSKCC

A lecture on sequence count data

A mass spectrometry imaging toolbox for statistical analysis

A metric to determine the biological quality of gene clusters

Analysis, exploration, manipulation, and visualization of Cufflinks high-throughput sequencing data.

Analysis for short time-series data

Analysis of CAGE (Cap Analysis of Gene Expression) sequencing data for precise mapping of transcription start sites and promoterome mining

Analysis of single and multiple phenomic data sets

Analysis of single-cell epigenomics datasets with a Shiny App

Analysis Tools for scATACseq Data with CoGAPS

Analytical R tools for Mass Spectrometry

Analyze flow cytometric data using gate information

Analyze flow cytometric data using histogram information

Analyze isomiRs and miRNAs from small RNA-seq

Analyze small RNA-seq count data

An Evolutionary Framework for the Identification and Study of Prognostic Gene Expression Signatures in Cancer

An Interactive Consensus Clustering Framework for Multi-platform Data Analysis

Annotation-Driven Clustering

An R package for analysis of case-control studies in genetic epidemiology

An R package for flow data clustering

An R package for qualitative biclustering in support of gene co-expression analyses

An R package for quantitative integration and analysis of multiple omics assays from heterogeneous samples

An R package for the analysis and result reporting of RNA-Seq data by combining multiple statistical algorithms

An R package for the Bayesian analysis of differential subcellular localisation experiments

An R Package for Time Course RNASeq Data Analysis

an R package for visualization of tree and annotation data

An R package to detect chromatin state switches from epigenomic data

A package for nonlinear dimension reduction with Isomap and LLE.

A pipeline especially built for computing several single-cell datasets

A pipeline for droplet-based single-cell RNA-seq data secondary analysis implemented in the drake Make-like toolkit for R language

Asessing statistical significance in predictive GWA studies

A Shiny App to accompany clusterExperiment

askoR - Differential Expresion Analysis using edgeR

Association analysis of CNVs and imputed SNPs incorporating uncertainty

A Tidy Transcriptomics introduction to RNA-Seq analyses

A time series clustering package combining slope and Frechet distances

A tool for differential expression analysis and DEGs based investigation to complex diseases by bi-clustering analysis

A Toolkit for Flow And Mass Cytometry Data

A tool to use GO Subtrees to Tag and Annotate Genes within a set

A unifying bioinformatics framework for spatial proteomics

A universal enrichment tool for interpreting omics data

Base Classes and Functions for Phylogenetic Tree Input and Output

Batch Effects Correction with Unknown Subtypes

Bayesian clustering and imputationa of single cell methylomes

Bayesian Hierarchical Clustering

Bayesian modelling of cell-to-cell DNA methylation heterogeneity

BEARscc (Bayesian ERCC Assesstment of Robustness of Single Cell Clusters)

Biclustering Analysis and Results Exploration

Big multivariate data plotted interactively

Brings Seurat to the Tidyverse

Brings SingleCellExperiment to the Tidyverse

Brings SummarizedExperiment to the Tidyverse

Brings transcriptomics to the tidyverse

Build Annotation From Online Database

Cancer Clone Finder

Cancer subtypes identification, validation and visualization based on multiple genomic data sets

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 OrderiNg by FluorEScence Signal

Cell Signalling Using Single Cell RNAseq Data Analysis

CEllular Latent Dirichlet Allocation

CHARGE: CHromosome Assessment in R from Gene Expression data

Cheminformatics Toolkit for R

chroGPS2: Generation, visualization and differential analysis of epigenome maps

Classes and Methods for "Class Discovery" with Microarrays or Proteomics

Classes and Methods for "Class Prediction" with Microarrays or Proteomics

Classes and Methods for Cross Validation of "Class Prediction" Algorithms

Classes and methods for cross validation of "class prediction" with microarrays or proteomics

Classes and methods for multi-omics data integration

Classes and Methods for Training and Using Binary Prediction Models

Classes and Methods to Use Genetic Algorithms for Feature Selection

Cluster analysis of Spatial Transcriptomics data

Cluster and Tree Conversion.

Clustering algorithm for ddPCR data

Clustering Algorithms for Bioconductor

Clustering and Alignment of ChIP-Seq peaks based on their shapes

Clustering and pathway analysis using exponential distributions

Clustering and Resolution Enhancement of Spatial Transcriptomes

Clustering and Visualizing Binary Matrices

Clustering and Visualizing Distance Matrices

Clustering and Visualizing RNA-Seq Expression Data using Grade of Membership Models

Clustering approach to solve complete Deconvolution problem

Clustering Comparison Package

Clustering Deviation Index (CDI)

Clustering, differential expression, and trajectory analysis for single- cell RNA-Seq

Clustering, Differential Expression, and Trajectory Analysis for Single-Cell RNA-Seq

Clustering for Flow Cytometry

Clustering of Genomic Regions Analysis Method

Clustering of high-throughput sequencing data by identifying co-expression patterns

Clustering of MS2 Spectra for Metabolite Identification

Clustering of Time Series Gene Expression data

Cluster Merging for Flow Cytometry Data

co-expressed gene-set enrichment analysis

Combines WGCNA and xCell readouts with bayesian network learrning to generate a Gene-Module Immune-Cell network (GMIC)

CommunityAMARETTO: A Computational Tool for the Discovery of Shared and Distinct Regulatory Mechanisms Across Biological Systems

Compare Clusterings for Single-Cell Sequencing

Comparing tumour copy number profiles

Comparison of disease and drug profiles using Gene set Enrichment Analysis

Comprehensive Analysis of Gene Interactivity Networks Based on Single-Cell RNA-Seq

Comprehensive and Interactive Analysis of Single Cell RNA-Seq Data

Comprehensive Annotation of Predictive Features for Interval-based Genomic Data

Computation of functional similarities between GO terms and gene products; GO enrichment analysis

Computation of Gene Expression-Based Signatures in Breast Cancer

Compute cluster stability scores for microarray data

Compute Mantel Cluster Correlations

Condition Comparison in scRNA-seq Data

Condition specific detection from expression data

ConsensusClusterPlus

Coordinated Gene Activity in Pattern Sets

CopyKit

Creates and uses physio spaces as a dimension reduction mapping

Creates diffusion maps

Creating annotated submodules of high-throughput data through recursive partitioning

cytofast - A quick visualization and analysis tool for CyTOF data

cytofkit2: an integrated mass cytometry data analysis pipeline. Cytofkit provides functions for data pre-processing, fast clustering, data visualization through linear or non-linear dimensionality reduction, automatic identification of cell subsets, and inference of the relatedness between cell subsets

cytofkit: an integrated mass cytometry data analysis pipeline

Cytometry Cluster Hierarchy and Cellular-to-phenotype Associations

Cytometry dATa anALYSis Tools

Data structures, clustering and testing for single cell immune receptor repertoires (scRNAseq RepSeq/AIRR-seq)

Decomposing Heterogeneous Cohorts using Omic Data Profiling

Delineate outstanding genomic zones of differential gene activity

deltaGseg

Detecting hidden batch factors through data adaptive adjustment for biological effects

Determination of essential phenotypic elements of clusters in high-dimensional entities

Develop and evaluate time series data models based on fluctuation based clustering

dgeAnalysis

Different distance measures

Differential abundance analysis with a right censored covariate in high-dimensional cytometry

Differential Analyis of Hi-C Data

Differential Analysis of Hi-C Data

Differential cell-type-specific allelic imbalance

Differential discovery in high-dimensional cytometry via high-resolution clustering

Differential Epigenetic Coregulation Test

Differential expression using kernel-based score test

Differential gene expression analysis based on the negative binomial distribution

Different methods for the integrative analysis multiple omics data

Dirichlet-Multinomial Mixture Model Machine Learning for Microbiome Data

Discern RNA structure proximal to protein binding

Discriminant Analysis for Evolutionary Inference

Display and manipulate heatmaps in clustergrammer.js

Dual redundant reference sequencing

Empirical Analysis of Digital Gene Expression Data in R

Evaluation of Bioinformatics Metrics

Example experimental data for use with the methyvim package

Exploration and Significant Biology on a Gene Set.

Exposome exploration and outcome data analysis

FABIA: Factor Analysis for Bicluster Acquisition

Fast and accurate scRNA-seq cell type identification

Fast and Interpretable Consensus Clustering via Minipatch Learning

fcScan for detecting clusters of coordinates with user defined options

FEAture SelcTion (FEAST) for Single-cell clustering

Finding Mutually Exclusive Groups of Alterations in Cancer Datasets

Finding the Number of Significant Principal Components

Find Specificity Groups with GLIPH and GLIPH2 Method

Find the most characteristic gene ontology terms for groups of human genes

Fingerprinting for Flow Cytometry

For Visualizing Differential Expression Analysis

Functional annotation-driven unsupervised clustering for single-cell data

Functional Enrichment analysis

Functional Gene Networks derived from biological enrichment analyses

Functional Network Analysis

Functional similarities

Functions to handle cDNA microarray data, including several methods of data analysis

Functions to help analyze data as phyloseq objects

GARS: Genetic Algorithm for the identification of Robust Subsets of variables in high-dimensional and challenging datasets

Gaussian mixture modeling for heavy-tailed distributions in Flow Cytometry data

Gene expression-based subtype classification for high-grade serous ovarian cancer

Generating Tree Hierarchy Visualizations from Gene Expression Data

GO-terms Semantic Similarity Measures

GPA (Genetic analysis incorporating Pleiotropy and Annotation)

graph-GPA: A graphical model for prioritizing GWAS results and investigating pleiotropic architecture

gRx Differential Clustering

Handling and analysis of high-throughput microbiome census data

hapFabia: Identification of very short segments of identity by descent (IBD) characterized by rare variants in large sequencing data

Heterogeneity-Induced Pre-Processing tOol

Hidden Factor Graph Models

Hierarchical Inference

Hierarchical Ordered Partitioning and Collapsing Hybrid (HOPACH)

Higher-Order Deconvolution Survival Analyses

HLA typing clustering and visualization based on specific similarity metrics

Human genome partitioning of dense sequencing data by identifying haplotype blocks

Identification Of Clinically Relevant Genomic Subtypes Using Outcome Weighted Learning

Identification of Mutational Clusters in 3D Protein Space via Simulation.

Identification of mutational clusters in protein quaternary structures.

Identification of Mutational Clusters in Proteins via a Graph Theoretical Approach.

Identification of Protein Amino acid Clustering

Identifies cell population in flow cytometry data.

Identify Different Architectures of Sequence Elements

Identify Moonlighting ncRNAs

ILoReg: a tool for high-resolution cell population identification from scRNA-Seq data

ImagingAMARETTO: tools for interpreting multi-omics networks for relevance to clinical outcomes and radiographic and histopathology imaging-derived biomarkers

immunoClust - Automated Pipeline for Population Detection in Flow Cytometry

Improving replicability in single-cell RNA-Seq cell type discovery

Inference and visualisation of Single-Cell RNA-seq data as a hierarchical tree structure

Inferring miRNA sponge modules in heterogeneous data

Infers biological signatures from gene expression data

Infers clonal composition of a tumor

Integrative clustering of multi-type genomic data

Interactive Analysis of Single Cell RNA-Seq Data

Interactive Differential Expresion Analysis Browser

Interactive SummarizedExperiment Explorer

Interpretation of RNA-seq experiments through robust, efficient comparison to public databases

Introduction to Tidy Transcriptomics

iSEE Universe

Iterative Binary Biclustering of Genesets

Iterative Clustering

Iterative Differential Clustering for single-cell

Iterative Pruning to Capture Population Structure

Iterative Pruning to Capture Population Structure version 2

Joint Inference of Mutually Exclusive Driver Pathways and their Progression Dynamics

Judging Quality of Clustering Methods using Mutual Information

Kernel-Based Analysis Of Biological Sequences

k-Means for k-Nearest Neighbors

LEA: an R package for Landscape and Ecological Association Studies

Linear model and normality based normalization and transformation method (Linnorm)

Linear Models for Microarray Data

Linear Subpsace identification to solve complete gene expression deconvolution problem

Machine Learning Interface for RNA-Seq Data

Machine learning tools for automated transcriptome clustering analysis

MAGAR: R-package to compute methylation Quantitative Trait Loci (methQTL) from DNA methylation and genotyping data

Make Biological Sense of Gene Set Enrichment Analysis Outputs

Marker Enrichment Modeling (MEM)

massiR: MicroArray Sample Sex Identifier

Massive correlating biclusters for gene expression data and associated methods

Matching and meta-clustering in flow cytometry

Merging of phenotype information from different cytometric profiles

MeSH Enrichment and Semantic analyses

MeSH(Medical Subject Headings) Semantic Similarity Measures

Metabarcoding and microbiome analysis using multiple amplicons

MetaCyto: A package for meta-analysis of cytometry data

Methods for Continuous Flow Cytometry

Methods for imaging mass cytometry data analysis

Methods for Single-Cell RNA-Seq Data Analysis

Methods for visualization and statistics on DNA methylation data

Microbial Community Analysis GUI

Microbial Comparative Genomics in R

Microbiome Exploration App

Mini-batch K-means Clustering for Single-Cell RNA-seq

Minimized Single-Cell Consensus Clustering

Mirsynergy

Miscellaneous Functions for Metabarcoding Analysis

Mismatch Tolerant Maximum Common Substructure Searching

Mixture modeling of single-cell RNA-seq data to identify genes with differential distributions

MLG Clustering

Model based analysis for paired-end data

Model-Based Comparative Analysis of the TCR Repertoire

Model higher-order methylation profiles

MOGAMUN: A Multi-Objective Genetic Algorithm to Find Active Modules in Multiplex Biological Networks

Molecular Signature identification using Biclustering

Monte Carlo Reference-based Consensus Clustering

multiClust: An R-package for Identifying Biologically Relevant Clusters in Cancer Transcriptome Profiles

Multi Omic Master Regulator Analysis

Multi-Omics integration and VIsualization in Cancer Subtyping

Multiple co-inertia analysis of omics datasets

Multiple omics data integrative clustering and gene set analysis

Multivariate analysis of microarray data using ADE4

Multivariate Correlation Estimator and Statistical Inference Procedures.

Murine Palate miRNA Expression Analysis

Mutation Order Prediction

Nearest Neighbor Detection for Bioconductor Packages

NetPathMiner for Biological Network Construction, Path Mining and Visualization

Network Analysis Supported by Boosting

Network smoothing for scRNAseq

Non-parametric Flow Cytometry Data Gating

OnASSIs Ontology Annotation and Semantic SImilarity software

Outlier-aware and Count-based Compositional Analysis of Single-cell Data.

Packaging common Seurat analysis tasks

Pancreatic Ductal Adenocarcinoma Tool-Kit

PCA Analysis and Visualization for Clustering

Permutation-Based Confidence for Molecular Classification

Phenotypic EMD for comparison of single-cell samples

Phenotyping of microbial Raman spectroscopy data

Phytoplankton Population Identification using Cell Pigmentation and/or Complexity

pipeComp pipeline benchmarking framework

Pipeline for augmented co-expression analysis

Pipelines for Bi-Clustering Using Matrix Factorization

Plot Gene Ontology and KEGG pathway Annotation and Abundance

Posterior association networks and functional modules inferred from rich phenotypes of gene perturbations

Precict cis-co-accessibility from single-cell chromatin accessibility data

preciseTAD: A machine learning framework for precise TAD boundary prediction

Predict cis-co-accessibility from single-cell chromatin accessibility data

Prediction of Protein Conserved Regions Using NADDA Algorithm

Prioritization of potentially bioactive metabolic features from epidemiological and environmental metabolomics datasets

Probabilistic inference for Nucleosome Positioning with MNase-based or Sonicated Short-read Data

Probabilistic inference of ChIP-seq

Probabilistic Outlier Identification for RNA Sequencing Generalized Linear Models

Projection-based Gating Strategy Optimization for Flow and Mass Cytometry

Promoter identification from large-scale TSS profiling data

Propagating Uncertainty in Microarray Analysis(including Affymetrix tranditional 3' arrays and exon arrays and Human Transcriptome Array 2.0)

Protein Micro Array Data Management and Interactive Visualization

Protein Profiling

Qualitative biclustering algorithm for expression data analysis in R

Quantification and Visualization of Variations of Splicing in Population

Quantification and Visulization of Variations of Splicing in Population

Rank Constrained Similarity Learning for single cell RNA sequencing data

Rank Constrained Similarity Learning for Single Cell RNA Sequencing Data

RBioinf

Read density map construction and accession. Visualization of ChIPSeq and RNASeq data sets

Reconstruction, visualization and analysis of branching trajectories

Reduce + Visualize GO

Reference-Based Single-Cell RNA-Seq Annotation

Refitting diploid region profiles using a clustering procedure

Regulatory Network Inference and Driver Gene Evaluation using Integrative Multi-Omics Analysis and Penalized Regression

Revealing differentially expressed genes using nonlinear dimensionality reduction for single cell RNA-Seq data

R interface to a subset of OpenBabel functionalities

RNA-seq analysis using multiple algorithms

RNASeqR: an R package for automated two-group RNA-Seq analysis workflow

R package for RIVER (RNA-Informed Variant Effect on Regulation)

R package for the statistical assessment of cell state hierarchies from single-cell RNA-seq data

R package motivated by the SCTC Dream Challenges

runibic: row-based biclustering algorithm for analysis of gene expression data in R

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

SCFA: Subtyping via Consensus Factor Analysis

sciCNV

ScRNA-seq Workflow CONCLUS - From CONsensus CLUSters To A Meaningful CONCLUSion

Select gold standard including positive and negative genes pairs based on the Gene Ontology

Selecting the number of mutational signatures using a perplexity-based measure and cross-validation

Semi-supervised adaptive-height snipping of the Hierarchical Clustering tree

Semi-Supervised Mixture Model

Sequential Flow Cytometry Data Gating

SigFuge

Signature-based Clustering for Diagnostic Purposes

Silly Putty Clustering

Similarity Identification in Gene Expression

Similarity measures for chemical compounds

SIMLR: Single-cell Interpretation via Multi-kernel LeaRning

simple Two-Tier Mapper: an interface for Two-Tier Mapper

Simplify Functional Enrichment Results

Single-Cell Consensus Clustering

Single-cell Interpretation via Multi-kernel LeaRning (SIMLR)

Single Cell Shiny Application for Analysing Single Cell Transcriptomics Data

Soft clustering of time series gene expression data

Somatic Signatures

SPADE -- An analysis and visualization tool for Flow Cytometry

SPADEVizR: an R package for Visualization, Analysis and Integration of SPADE results

Spatial Analysis of Network Associations

spatialHeatmap

spatialHeatmap: Visualizing Spatial Assays in Anatomical Images and Large-Scale Data Extensions

Spatial Image Analysis of Tissues

Spatial transcriptomic clustering

Spatial Transcriptomics Analysis

SpectralTAD: Hierarchical TAD detection using spectral clustering

spsBio: A systemPipeShiny plugin for biological data visualization

statistical analysis and visualization of functional profiles for genes and gene clusters

Statistical analysis for sparse high-throughput sequencing

Statistical Analysis of the GeneChip

Statistical inference based on the Sorensen-Dice dissimilarity and the Gene Ontology (GO)

Statistical Inference of Associations between Microbial Communities And host phenoTypes

stJoincount - Join count statistic for quantifying spatial correlation between clusters

Subtype Identification with Survival Data

supraHex: a supra-hexagonal map for analysing tabular omics data

systemPipeShiny: An Interactive Framework for Workflow Management and Visualization

TADCompare: Identification and characterization of differential TADs

Targeted, Robust, and Model-free Differential Methylation Analysis

The ClusterSignificance package provides tools to assess if class clusters in dimensionality reduced data representations have a separation different from permuted data

The scigenex package (Single-Cell Informative GENe Explorer)

The tidyomics blog

Threshing and Reaping for Principal Components

Tidy Transcriptomics for Single-cell RNA Sequencing Analyses

Time-Course Multi-Omics data integration

Time course sequencing data analysis

Time sensitive microRNA-mRNA integration, analysis and network generation tool

Time Series Clustering of Gene Expression with Gaussian Mixed-Effects Models and Smoothing Splines

TNBC.CMS: Prediction of TNBC Consensus Molecular Subtypes

Tomo-seq data analysis

Tools for analyzing Micro Array experiments

Tools for Assessing Clustering

Tools for curating, analyzing, and manipulating biological sequences

Tools for data visualization

Tools for microbiome analysis

Tools for Omics Data Analysis

Tools for ordering single-cell sequencing

Tools for Working With Synteny Objects

Tools to test association between gene expression and phenotype in a way that is efficient, structured, fast and scalable. We also provide tools to do GSEA (Gene set enrichment analysis) and copy number variation.

trajectory-based differential expression analysis for sequencing data

Transcriptional analysis based on transcriptograms

TRONCO, an R package for TRanslational ONCOlogy

TSS sequencing data analysis

Two-Tier Mapper: a clustering tool based on topological data analysis

Unbiased Extraction of Single Cell gene signatures using Multiple Correspondence Analysis

Unbiased Extraction of Single Cell Identity using Multiple Correspondence Analysis

Unified Approach for Simultaneous Gene Clustering and Differential Expression Identification

Uniform interfaces to R machine learning procedures for data in Bioconductor containers

Using Cytogenetics Data in R

Using self-organizing maps for visualization and interpretation of cytometry data

ViSEAGO: a Bioconductor package for clustering biological functions using Gene Ontology and semantic similarity

ViSEAGO: Easier data mining of biological functions organized into clusters using Gene Ontology and semantic similarity

Visual and interactive gene expression analysis

Visual comparison of mutational processes in a set of tumors

Visualise microarray and RNAseq data using gene ontology annotations

Visualization of Phylogenetic Networks

What the Package Does (One Line, Title Case)

What the Package Does TODOELI

Word cloud summaries of GO enrichment analysis

YARN: Robust Multi-Condition RNA-Seq Preprocessing and Normalization

Yet Another Package for Signature Analysis

Yet Another Single-Cell Analysis Toolkit (Yeskit)

Biocview "Clustering"

R Package Documentation

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