Biocview "FeatureExtraction"

A comprehensive R package for managing and analyzing microbiome and other ecological data within the tidy framework

Adjacency-Constrained Clustering of a Block-Diagonal Similarity Matrix

A Hybrid Feature Selection method for gene expression data

Analysis of Brain Imaging Data

An Interactive Consensus Clustering Framework for Multi-platform Data Analysis

an R package for analysis, visualization and biomarker discovery of microbiome

A package for nonlinear dimension reduction with Isomap and LLE.

A package to extract spatial features based on multiplex IF images

a region-based method for quantitating the conservation and divergence of methylation patterns between species by high order features

A sensitive and fast tool for detection of TAD boundaries

A suite of functions to facilitate zFPKM transformations

A tool for quantification of associations between genotypes and phenotypes in genome wide association studies (GWAS) with Bayesian inference and statistical learning

A t-SNE framework to visualize OMICs data

Batch Effects Correction with Unknown Subtypes

Bayesian clustering and imputationa of single cell methylomes

Bayesian modelling of cell-to-cell DNA methylation heterogeneity

Binned Motif Enrichment Analysis and Visualization

Candidate Driver Analysis

Classification and Feature Selection for 'Omics' Datasets

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

Comprehensive Annotation of Predictive Features for Interval-based Genomic Data

Comprehensive Pipeline for Analyzing and Visualizing Array-Based CGH Data

Computational pipeline for computing probability of modification from structure probing experiment data

Context-Aware Transcript Quantification from Long Read RNA-Seq data

Decomposing Heterogeneous Cohorts using Omic Data Profiling

Deconvolution of mixed cells from spatial and/or bulk gene expression data

Detection of cell-type-specific risk-CpG sites in epigenome-wide association studies

Detection of clonally exclusive gene or pathway pairs in a cohort of cancer patients

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

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

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

Differentially Expressed Gene-Gene pairs

Evaluation of Bioinformatics Metrics

Fast and Interpretable Consensus Clustering via Minipatch Learning

Fast Correlation Based Filter for Feature Selection

FEAture SelcTion (FEAST) for Single-cell clustering

Fit transcriptional regulatory networks using gene expression, priors, machine learning

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

Generating Various Molecular Representations for Chemicals, Proteins, DNAs, RNAs and Their Interactions

Generating Various Molecular Representations for Chemicals, Proteins, DNAs/RNAs and Their Interactions

Genome wide association studies of multiple traits with Bayesian multilvel models

genphen: tool for quantification of genotype-phenotype associations in genome wide association studies (GWAS)

gin in R

GWAS Incorporating Networks

Hits Selection for Synthetic Lethal RNAi Screen Data

Identify Different Architectures of Sequence Elements

Integrative Pathway Analysis with Modern PCA Methodology and Gene Selection

Interactive SummarizedExperiment Explorer

Interactive visualization of scRNA-seq data with Cerebro

iSEE Universe

Iteratively Adjusted Surrogate Variable Analysis

KnowSeq R/Bioc package: The Smart Transcriptomic Pipeline

Michaelis-Menten Modelling of Dropouts in single-cell RNASeq

'(m,n)-mer' - A Simple Statistical Feature for Sequence Classification

Model higher-order methylation profiles

Molecular Informatics Toolkit for Compound-Protein Interaction in Drug Discovery

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

Multi Omic Master Regulator Analysis

Network-Regularized Regression Models

Packaging common Seurat analysis tasks

preciseTAD: A machine learning framework for precise TAD boundary prediction

Predict open reading frames in nucleotide sequences

Quantification of the Tumor Immune contexture from RNA-seq data

Reference-guided isoform reconstruction and quantification for long read RNA-Seq data

sigFeature: Significant feature selection using SVM-RFE & t-statistic

Signature-based Clustering for Diagnostic Purposes

Signature discovery from omics data

Single Cell Shiny Application for Analysing Single Cell Transcriptomics Data

SpectralTAD: Hierarchical TAD detection using spectral clustering

Statistical analysis of RNA editing sites and hyper-editing regions

Statistical Inference of Associations between Microbial Communities And host phenoTypes

Suffix Array Kernel Smoothing for discovery of correlative sequence motifs and multi-motif domains

Summarize, Analyze and Visualize MAF Files

Supervised mutational signatures

TADCompare: Identification and characterization of differential TADs

Time-Course Multi-Omics data integration

Tools for region- and process-centric analyses of multiple assay types

Tree Aggregation

Variable Selection Oriented LASSO Bagging Algorithm

Biocview "FeatureExtraction"

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