Biocview "Normalization"

A collection of tools for imaging MS data processing

A Comprehensive R Package For Analyzing Quantitative Phosphoproteomics Data

Adjust for positional and batch effects using ComBat

A DownStream Chemo-Proteomics Analysis Pipeline

A fast scatterplot smoother suitable for microarray normalization

Algorithms for Calculating Microarray Enrichment (ACME)

alpine

A mass spectrometry imaging toolbox for statistical analysis

Analysing Illumina HumanMethylation BeadChip Data

Analysis for short time-series data

Analysis, interpretation, and visualization of DamID-seq data

Analysis of Brain Imaging Data

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

Analysis of Cap Analysis of Gene Expression (CAGE) data using Bioconductor

Analysis of compositions of microbiomes with bias correction

Analysis of single and multiple phenomic data sets

Analysis of single-cell epigenomics datasets with a Shiny App

Analytical R tools for Mass Spectrometry

Analyze Illumina Infinium DNA methylation arrays

An integrated analysis package of miRNA and mRNA expression data

An Interactive Consensus Clustering Framework for Multi-platform Data Analysis

A normalization and copy number estimation method for single-cell DNA sequencing

A Normalization and Copy Number Variation Detection Method for Whole Exome Sequencing

A normalization-invariant minimum enclosing ball method to detect differentially expressed genes for RNA-seq data

A normalization method for Copy Number Aberration in cancer samples

An R package estimates the correlations of orthologs and transposable elements between two species

An R package for analysis of massive parallel sequencing based RNA structure probing data

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 of Data Importing, Processing and Analysis for Opera High Content Screening System

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

A pipeline for processing drug sensitivity screen data

ascend - Analysis of Single Cell Expression, Normalisation, and Differential expression

askoR - Differential Expresion Analysis using edgeR

Assay characterization: estimation of limit of blanc(LoB) and limit of detection(LOD)

A statistical normalization method and differential expression analysis for RNA-seq data between different species

Asymmetric Within-Sample Transformation

A test for when to use quantile normalization

A Tidy Transcriptomics introduction to RNA-Seq analyses

a tool to perform statistical analysis of differential protein expression for quantitative proteomics data.

AUCell: Analysis of 'gene set' activity in single-cell RNA-seq data (e.g. identify cells with specific gene signatures)

A wrapper for Gemma's Restful API to access curated gene expression data and differential expression analyses

Bandwise normalization and batch correction of Hi-C data

Base NanoString Experiment Class

Batch Effects Quality Control Software

Bayesian Analysis of Single-Cell Sequencing data

Benchmark of differential abundance methods on microbiome data

Bias Awared Peak Calling and Quantification for MeRIP-Seq

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

CGH Micro-Array NORmalization

Chip Analysis Methylation Pipeline for Illumina HumanMethylation450 and EPIC

ChIP-Seq Analysis with Windows

ChIP-Seq data scaling according to spike-in control

Chip-seq Signal Quantifier Pipeline

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

coexnet: An R package to build CO-EXpression NETworks from Microarray Data

Coexpression for Transcription Factors using Regulatory Impact Factors and Partial Correlation and Information Theory analysis

Comparing Differential Abundance/Expression Methods

Compensates for the bias introduced by median normalization in phosphoproteomics. This is done by taking enriched and non-enriched data and creating a normalization factor.

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

Comprehensive and Interactive Analysis of Single Cell RNA-Seq Data

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

CopyKit

Copy Number Analysis for 450k Illumina Methylation Arrays

Count model based differential expression and normalization on GeoMx RNA data

Cytometry dATa anALYSis Tools

Data Mining and Analysis of Lipidomics Datasets

Data normalization by matrix raking

Data preprocessing and quality control for Illumina HumanMethylation450 and MethylationEPIC BeadChip (USC version)

DegNorm: degradation normalization for RNA-seq data

DEsubs: an R package for flexible identification of differentially expressed subpathways using RNA-seq expression experiments

Detecting hidden batch factors through data adaptive adjustment for biological effects

dgeAnalysis

Differential Abundance Analysis of Label-Free Mass Spectrometry Data

Differential Analyis of Hi-C Data

Differential Analysis of Hi-C Data

Differential Binding Estimation for Protein Complexes

Differential Expression Analysis of NanoString nCounter Data

Differential gene expression analysis based on the negative binomial distribution

Differentially Expressed Heterogeneous Overdispersion Gene Test for Count Data

Differential pattern analysis for Ribo-seq data

Diffusion scores on biological networks

Discriminant Analysis for Evolutionary Inference

Empirical Analysis of Digital Gene Expression Data in R

Enhanced copy-number variation analysis using Illumina DNA methylation arrays

Evaluation of normalization methods and calculation of differential expression analysis statistics

Experimental Design in Differential Abundance analysis

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

Fast Methylome-Wide Association Study Pipeline for Enrichment Platforms

Fast treatment of MACSQuantify FACS data

Feature Specific Quantile Normalization

Feature-Wise Normalization for Microbiome Sequencing Data

Filter replicated high-throughput transcriptome sequencing data

Fishpond: differential transcript and gene expression with inferential replicates

Fishpond: downstream methods and tools for expression data

Functions used to preprocess datasets stored in BioDataome

Generally applicable transcriptome-wide analysis of translational efficiency using anota2seq

Generate Quality Surrogate Variable Analysis for Degradation Correction

Gene set analysis accounting for gene-gene correlations

Gene set analysis following differential expression using linear (mixed) modeling with dream

GUI for limma Package with Affymetrix Microarrays

GUI for limma Package With Two Color Microarrays

HiCcompare: Joint normalization and comparative analysis of multiple Hi-C datasets

HiCdiff: Joint normalization and comparative analysis of multiple Hi-C datasets

Hi-C Direct Caller Plus

Higher-Order Deconvolution Survival Analyses

Identifying genetic trait/phenotype relevant cell type/state at single cell resolution

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

Infers biological signatures from gene expression data

Integrative Analysis Pipeline for Pooled CRISPR Functional Genetic Screens

Introduction to Tidy Transcriptomics

Intron-Exon Retention Estimator

IP-seq data analysis and vizualization

Iterative Differential Clustering for single-cell

KnowSeq R/Bioc package: The Smart Transcriptomic Pipeline

Landscape Expression Visualization Interface

LC/MS Metabolomics Data Processing Utilities

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

Linear Models for Microarray Data

LiP Significance Analysis in shotgun mass spectrometry-based proteomic experiments

LPEseq: local-pooled-error test for RNA-seq data with a small number of replicates

Maaslin2

Maximum Likelihood Decay Modeling of RNA Degradation Data

Mean Alterations Using Discrete Expression

Mean/Median-balanced quantile normalization

Methods for Single-Cell RNA-Seq Data Analysis

Methylation Enriched LOci Normalization (MELON) for genome-wide DNA methylation experiments

Microarray Analysis of Differential Expression

Microarray and RNA-seq Processing for ImmuneSpace

Microbiome differential abudance and correlation analyses with bias correction

Microbiome Exploration App

MRS Data Preprocessing and Normalisation

Multi-Dataset Model-based Differential Expression Proteomics Analysis Platform

Multi matrix analysis of multiple proteomics datasets on peptide level

"Multivariable Association Discovery in Population-scale Meta-omics Studies"

Multivariate Information Criteria to identify important predictors in high dimensional multivariate regression

Muscle Epigenetic Age Test

NanoString data normalization and differential gene expression analysis

NanoString GeoMx Tools

Network smoothing for scRNAseq

Normalization and difference calling in ChIP-seq data

Normalization of Mass Spectrometry Data

Normalization of Single-Cell mRNA Sequencing Data

Normalization of single cell RNA-seq data

Normalization Procedure for Infinium HumanMethylation450 BeadChip Kit

Normalize and detect differences between Hi-C datasets when replicates of each experimental condition are available

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

Permutation-Based Confidence for Molecular Classification

PKG_TITLE

PLSDA-batch

Post Translational Modification (PTM) Significance Analysis in shotgun mass spectrometry-based proteomic experiments with tandem mass tag (TMT) labeling

Predicting Disease Progression Based on Methylation Correlated Blocks using Ensemble Models

Preprocessing, analyzing, and reporting of RNA-seq data

Preprocessing of Illumina Infinium 450K data

Probabilistic Outlier Identification for RNA Sequencing Generalized Linear Models

Protein Micro Array Data Management and Interactive Visualization

Protein Significance Analysis in DDA, SRM and DIA for Label-free or Label-based Proteomics Experiments

Proteomics Label Free Quantification

Provides a GUI for DAPAR

Quality control and analysis tools for Illumina DNA methylation BeadChip

Quality Control for Single-Cell RNA-seq Data

Quality metrics and data processing methods for NanoString mRNA gene expression data

Quantify and interpret divers of variation in multilevel gene expression experiments

Quantify and interpret drivers of variation in multilevel gene expression experiments

Quantitative Metabolomics Data Processing Tools

Random Rotation Methods for High Dimensional Data with Batch Structure

Rcpp Integration Surrogate Variable Analysis

Recovering spatially-varying cell-specific gene co-expression networks for single-cell spatial expression data.

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

Refitting diploid region profiles using a clustering procedure

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

Reliable CNV detection in targeted sequencing applications

Removal of unwanted variation for gene-gene correlations and related analysis

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

R Normalization and Inference of Time Series data

Robust outlier identification for DNA methylation data

Robust statistical inference for quantitative LC-MS proteomics

R Package for Processing High Content Screening data

RUV for normalization of expression array data

Scalable differential expression analysis of single cell transcriptomics datasets with complex study designs

Scaling normalization based on the Pareto distribution

scMerge: Merging multiple batches of scRNA-seq data

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

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 Overview of Normalized Expression data

Single-Cell RNA-Seq Analysis Utilities

Single-cell RNA sequencing data normalization

Single Cell Shiny Application for Analysing Single Cell Transcriptomics Data

Small-Count Analysis Methods for High-Dimensional Data

Smooth quantile normalization

Spatial quantile normalization

Spatial transcriptome analyses of Nanostring's DSP data in R

Spatial Transcriptomics Analysis

Spike-in calibration for cell-free MeDIP

Stan implementation of BASiCS

Statistical analysis for sparse high-throughput sequencing

Statistical Analysis of Molecular Profiles

Statistical approaches for differential expression analysis in metatranscriptomics

Statistical Characterization of Post-translational Modifications

Statistics and dIagnostic Graphs for HTS

Suite of Functions for Pooled Crispr Screen QC and Analysis

Surrogate Variable Analysis

Survival analysis for gene signatures

SVAPLSseq-An R package to adjust for the hidden factors of variability in differential gene expression studies based on RNAseq data

SVAPLSseq-An R package to estimate the hidden factors of unwanted variability and adjust for them to enable a more powerful and accurate differential expression analysis based on RNAseq data

The removal of batch effects from datasets using a PCA and constrained optimisation based technique

The tidyomics blog

Tidy Transcriptomics for Single-cell RNA Sequencing Analyses

Tools for Assessing Clustering

Tools for Diagnostics and Corrections of Batch Effects in Proteomics

Tools for Metabolomics Data

Tools for Omics Data Analysis

Tools for processing of high-dimensional cytometry data

Tools for qPLEX-RIME data analysis

Tools for quantitative proteomics data analysis

Tools for the Differential Analysis of Proteins Abundance with R

Tools for the Efficient Analysis of High-Resolution Genomics Data

Tools for the preprocessing and analysis of the Illumina microarrays on the detector (bead) level

TSS sequencing data analysis

UMI4Cats: Processing, analysis and visualization of UMI-4C chromatin contact data

Unbiased Extraction of Single Cell Identity using Multiple Correspondence Analysis

User-friendly Workflow for Pre-processing and Statistical Analysis of Mass Spectrometry Data

Variance Stabilizing Transformation for Gamma-Poisson Models

Visual and interactive gene expression analysis

Visualization of highly multiplexed imaging data in R

What the Package Does (One Line, Title Case)

Wrench normalization for sparse count data

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

Biocview "Normalization"

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