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
Adjust for positional and batch effects using ComBat
A DownStream Chemo-Proteomics Analysis Pipeline
A DownStream Chemo-Proteomics Analysis Pipeline
A fast scatterplot smoother suitable for microarray normalization
Algorithms for Calculating Microarray Enrichment (ACME)
alpine
alpine
A mass spectrometry imaging toolbox for statistical analysis
Analysing Illumina HumanMethylation BeadChip Data
Analysis for short time-series data
Analysis for short time-series data
Analysis for short time-series data
Analysis, interpretation, and visualization of DamID-seq 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 CAGE (Cap Analysis of Gene Expression) sequencing data for precise mapping of transcription start sites and promoterome mining
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 Cap Analysis of Gene Expression (CAGE) data using Bioconductor
Analytical R tools for Mass Spectrometry
Analytical R tools for Mass Spectrometry
Analytical R tools for Mass Spectrometry
Analyze Illumina Infinium DNA methylation arrays
Analyze Illumina Infinium DNA methylation arrays
Analyze Illumina Infinium DNA methylation arrays
An integrated analysis package of miRNA and mRNA expression data
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 Variation Detection Method for Whole Exome Sequencing
A normalization method for Copy Number Aberration in cancer samples
An R package for analysis of massive parallel sequencing based RNA structure probing data
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 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 R package to extract knowledge by using RNA-seq raw files
ascend - Analysis of Single Cell Expression, Normalisation, and Differential expression
A statistical normalization method and differential expression analysis for RNA-seq data between different species
A statistical normalization method and differential expression analysis for RNA-seq data between different species
A test for when to use quantile normalization
A test for when to use quantile normalization
a tool to perform statistical analysis of differential protein expression for quantitative proteomics data.
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)
AUCell: Analysis of 'gene set' activity in single-cell RNA-seq data (e.g. identify cells with specific gene signatures)
Bandwise normalization and batch correction of Hi-C data
Bandwise normalization and batch correction of Hi-C data
Bayesian Analysis of Single-Cell Sequencing data
Bayesian Analysis of Single-Cell Sequencing data
Big multivariate data plotted interactively
Big multivariate data plotted interactively
Big multivariate data plotted interactively
Chip Analysis Methylation Pipeline for Illumina HumanMethylation450 and EPIC
Chip Analysis Methylation Pipeline for Illumina HumanMethylation450 and EPIC
Chip Analysis Methylation Pipeline for Illumina HumanMethylation450 and EPIC
Chip Analysis Methylation Pipeline for Illumina HumanMethylation450 and EPIC
Chip Analysis Methylation Pipeline for Illumina HumanMethylation450 and EPIC
Chip Analysis Methylation Pipeline for Illumina HumanMethylation450 and EPIC
ChIP-Seq Analysis with Windows
ChIP-Seq Analysis with Windows
ChIP-Seq data scaling according to spike-in control
ChIP-Seq data scaling according to spike-in control
coexnet: An R package to build CO-EXpression NETworks from Microarray Data
coexnet: An R package to build CO-EXpression NETworks from Microarray Data
coexnet: An R package to build CO-EXpression NETworks from Microarray Data
Comparing Differential Abundance/Expression Methods
Compensates for the bias introduced by median normalization in phosphoproteomics
Copy Number Analysis for 450k Illumina Methylation Arrays
Cytometry dATa anALYSis Tools
Cytometry dATa anALYSis Tools
Data Mining and Analysis of Lipidomics Datasets
Data preprocessing and quality control for Illumina HumanMethylation450 and MethylationEPIC BeadChip
Data preprocessing and quality control for Illumina HumanMethylation450 and MethylationEPIC BeadChip
Data preprocessing and quality control for Illumina HumanMethylation450 and MethylationEPIC BeadChip (USC version)
DEsubs: an R package for flexible identification of differentially expressed subpathways using RNA-seq expression experiments
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
Detecting hidden batch factors through data adaptive adjustment for biological effects
Detecting hidden batch factors through data adaptive adjustment for biological effects
Detecting hidden batch factors through data adaptive adjustment for biological effects
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 Expression Analysis of NanoString nCounter Data
Differential gene expression analysis based on the negative binomial distribution
Differential gene expression analysis based on the negative binomial distribution
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
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
Factorial Latent Variable Modeling of Single-Cell RNA-Seq Data
Factorial Latent Variable Modeling of Single-Cell RNA-Seq Data
Fast Methylome-Wide Association Study Pipeline for Enrichment Platforms
Fast Methylome-Wide Association Study Pipeline for Enrichment Platforms
Fast treatment of MACSQuantify FACS data
Feature Specific Quantile Normalization
Filter replicated high-throughput transcriptome sequencing data
Filter replicated high-throughput transcriptome sequencing data
Fishpond: differential transcript and gene expression with inferential replicates
Fishpond: differential transcript and gene expression with inferential replicates
Functions used to preprocess datasets stored in BioDataome
Generally applicable transcriptome-wide analysis of translational efficiency using anota2seq
Generally applicable transcriptome-wide analysis of translational efficiency using anota2seq
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
HiCcompare: Joint normalization and comparative analysis of multiple Hi-C datasets
HiCdiff: Joint normalization and comparative analysis of multiple Hi-C datasets
Infers biological signatures from gene expression data
Integrative analysis pipeline for pooled CRISPR functional genetic screens
Integrative analysis pipeline for pooled CRISPR functional genetic screens
Intron-Exon Retention Estimator
Intron-Exon Retention Estimator
IP-seq data analysis and vizualization
IP-seq data analysis and vizualization
Linear model and normality based transformation method (Linnorm)
Linear Models for Microarray Data
Lipidomics Analysis Workflow in R
LPEseq: local-pooled-error test for RNA-seq data with a small number of replicates
LPEseq: local-pooled-error test for RNA-seq data with a small number of replicates
Maaslin2
Maaslin2
Maximum Likelihood Decay Modeling of RNA Degradation Data
Maximum Likelihood Decay Modeling of RNA Degradation Data
Mean/Median-balanced quantile normalization
Methods for Single-Cell RNA-Seq Data Analysis
Methods for Single-Cell RNA-Seq Data Analysis
Methylation Enriched LOci Normalization (MELON) for genome-wide DNA methylation experiments
Microarray Analysis of Differential Expression
Multi-Dataset Model-based Differential Expression Proteomics Analysis Platform
Multi-Dataset Model-based Differential Expression Proteomics Analysis Platform
Multi matrix analysis of multiple proteomics datasets on peptide level
NanoString data normalization and differential gene expression analysis
Network smoothing for scRNAseq
Network smoothing for scRNAseq
Normalization and difference calling in ChIP-seq data
Normalization and difference calling in ChIP-seq data
Normalization of Mass Spectrometry Data
Normalization of single cell RNA-seq data
Normalization of single cell RNA-seq data
Normalization Procedure for Infinium HumanMethylation450 BeadChip Kit
Normalization Procedure for Infinium HumanMethylation450 BeadChip Kit
Normalize and detect differences between Hi-C datasets when replicates of each experimental condition are available
Normalize and detect differences between Hi-C datasets when replicates of each experimental condition are available
Normalize and detect differences between Hi-C datasets when replicates of each experimental condition are available
Normalize and detect differences between Hi-C datasets when replicates of each experimental condition are available
Permutation-Based Confidence for Molecular Classification
Preprocessing of Illumina Infinium 450K data
Protein Significance Analysis in DDA, SRM and DIA for Label-free or Label-based Proteomics Experiments
Protein Significance Analysis in DDA, SRM and DIA for Label-free or Label-based Proteomics Experiments
Provides a GUI for DAPAR
Provides a GUI for DAPAR
Provides a GUI for DAPAR
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 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 divers of variation in multilevel gene expression experiments
Rcpp Integration Surrogate Variable Analysis
Regulatory Network Inference and Driver Gene Evaluation using Integrative Multi-Omics Analysis and Penalized Regression
Regulatory Network Inference and Driver Gene Evaluation using Integrative Multi-Omics Analysis and Penalized Regression
Reliable CNV detection in targeted sequencing applications
Reliable CNV detection in targeted sequencing applications
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
RNASeqR: an R package for automated two-group RNA-Seq analysis workflow
RNASeqR: an R package for automated two-group RNA-Seq analysis workflow
R Normalization and Inference of Time Series data
R Normalization and Inference of Time Series data
R Package for Processing High Content Screening data
R Package for Processing High Content Screening data
R Package for Processing High Content Screening data
RUV for normalization of expression array data
scMerge: Merging multiple batches of scRNA-seq data
scMerge: Merging multiple batches of scRNA-seq data
sigFeature: Significant feature selection using SVM-RFE & t-statistic
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 Analysis Toolkit for Gene Expression Data in R
Single-Cell Batch Correction Methods
Single-Cell Batch Correction Methods
Single Cell Overview of Normalized Expression data
Single Cell Overview of Normalized Expression data
Single-cell RNA sequencing data normalization
Single-cell RNA sequencing data normalization
Single Cell Shiny Application for Analysing Single Cell Transcriptomics Data
Smooth quantile normalization
Smooth quantile normalization
Smooth quantile normalization
Spatial Transcriptomics Analysis
Statistical analysis for sparse high-throughput sequencing
Statistical analysis for sparse high-throughput sequencing
Statistical Analysis of Molecular Profiles
Statistical Analysis of Molecular Profiles
Statistics and dIagnostic Graphs for HTS
Statistics and dIagnostic Graphs for HTS
Suite of Functions for Pooled Crispr Screen QC and Analysis
Suite of Functions for Pooled Crispr Screen QC and Analysis
Surrogate Variable 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 removal of batch effects from datasets using a PCA and constrained optimisation based technique
Tools for Diagnostics and Corrections of Batch Effects in Proteomics
Tools for Diagnostics and Corrections of Batch Effects in Proteomics
Tools for qPLEX-RIME data analysis
Tools for qPLEX-RIME data analysis
Tools for the Differential Analysis of Proteins Abundance with R
Tools for the Differential Analysis of Proteins Abundance with R
Tools for the preprocessing and analysis of the Illumina microarrays on the detector (bead) level
Unbiased Extraction of Single Cell Identity using Multiple Correspondence Analysis
Visual and interactive gene expression analysis
Visual and interactive gene expression analysis
Visual and interactive gene expression analysis
Wrench normalization for sparse count data
Wrench normalization for sparse count data
YARN: Robust Multi-Condition RNA-Seq Preprocessing and Normalization
YARN: Robust Multi-Condition RNA-Seq Preprocessing and Normalization