Biocview "DimensionReduction"

A dimensionality reduction tool using gene detection pattern to mitigate noisy expression profile of scRNA-seq

A Functional Approach To Impute Genetically Regulated Expression

A metric to determine the biological quality of gene clusters

An alignment and integration method for single cell genomics

Analysis Tools for scATACseq Data with CoGAPS

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

A package for nonlinear dimension reduction with Isomap and LLE.

Association Plots

A t-SNE framework to visualize OMICs data

Binomial Random Forest Feature Selection

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 type annotation for unannotated single-cell RNA-Seq data

Classes and methods for multi-omics data integration

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

Clustering of (epigenetic) DNA methylation data using a variational Bayes NMF algorithm

Compositional omics model based visual integration

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

Coordinated Gene Activity in Pattern Sets

Correspondence Analysis for Single Cell Data

Creates and uses physio spaces as a dimension reduction mapping

Creation and Analysis of Pathway Expression Profiles (PEPs)

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

Data-Adaptive Statistics for High-Dimensional Multiple Testing

Density-Preserving Data Visualization via Non-Linear Dimensionality Reduction

Detection of cell-cell interaction from single-cell RNA-seq dataset by tensor decomposition

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

Evaluate Reduced Dimension Representations

Exploratory Analysis of ATAC-seq data

Factorial Latent Variable Modeling of Single-Cell RNA-Seq Data

Find microbial interactions

Fit row-column association models with the negative binomial distribution for the microbiome

GENetic EStimation and Inference in Structured samples (GENESIS): Statistical methods for analyzing genetic data from samples with population structure and/or relatedness

Genotype Conditional Association TEST

Global Test for Counts

Handling Missing Individuals in Multi-Omics Data Integration

Hexbin plots for single cell omics data

Identify Different Architectures of Sequence Elements

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

Infers biological signatures from gene expression data

Integrative Pathway Analysis with Modern PCA Methodology and Gene Selection

Interactive SummarizedExperiment Explorer

Interactive Visualization of RNA-seq Data Using a Principal Components Approach

interface to python sklearn via Rstudio reticulate

iSEE Universe

Logistic Factor Analysis for Categorical Data

Matched Interaction across Tissues (MIxT) data analysis

Michaelis-Menten Modelling of Dropouts in single-cell RNASeq

Minimized Single-Cell Consensus Clustering

Modularized and interactive analyses over a FacileDataStore

Multi-Omics Factor Analysis (MOFA)

Multi-Omics Factor Analysis v2

Multivariate analysis of microarray data using ADE4

Network Analysis Supported by Boosting

Network Centrality Metrics for Elastic-Net Regularized Models

Network smoothing for scRNAseq

One-Dimensional Soli-Expression by Nonlinear Stochastic Embedding (OneSENSE)

ontological exploration of scRNA-seq of 1.3 million mouse neurons from 10x genomics

Out-of-core statistical computing and signal processing

Phenotypic EMD for comparison of single-cell samples

PhyloProfile

Pipelines for Bi-Clustering Using Matrix Factorization

PLSDA-batch

projection comparison app

Quality Control for Single-Cell RNA-seq Data

Quantitative Metabolomics Data Processing Tools

Rank Constrained Similarity Learning for single cell RNA sequencing data

Rank Constrained Similarity Learning for Single Cell RNA Sequencing Data

Reconstruction, visualization and analysis of branching trajectories

R package for sparse and out-of-core arithmetic and decomposition of Tensor

R wrapper for the python openTSNE library

Shiny-based interactive data-quality exploration for omics data

Shiny graphical interface and command-line for Regularized (or Sparse) Generalized Canonical Correlation Analysis (R/SGCCA)

Single-cell analysis toolkit for gene expression data in R

Single-Cell Analysis Toolkit for Gene Expression Data in R

Single-Cell Consensus Clustering

Single-Cell Data Visualisation Using Kernel Gene-Weighted Density Estimation

Single Cell Shiny Application for Analysing Single Cell Transcriptomics Data

Singular Value Decomposition for Bioconductor Packages

Small-Count Analysis Methods for High-Dimensional Data

Spatial transcriptomic clustering

ssPATHS: Single Sample PATHway Score

Stabilised mosaic single cell data integration using unshared features

Statistical analysis of RNA editing sites and hyper-editing regions

Time-Course Multi-Omics data integration

Tools for Assessing Clustering

Tools for matrices with precision weights, test and explore weighted or sparse data

Tools for Omics Data Analysis

tricycle: Transferable Representation and Inference of cell cycle

Unbiased Extraction of Single Cell gene signatures using Multiple Correspondence Analysis

Unbiased Extraction of Single Cell Identity using Multiple Correspondence Analysis

Unified Statistical Modeling of Omics Data

Variable Selection in Finite Mixture of AFT Regression and FMR

Varying-Censoring Aware Matrix Factorization

VeloViz: RNA-velocity informed 2D embeddings for visualizing cell state trajectories

Visualization functions for spatial transcriptomics data

Visualizations of expressionSet Bioconductor object

Zero-Inflated Negative Binomial Model for RNA-Seq Data

Biocview "DimensionReduction"

R Package Documentation

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