Biocview "Normalization"

Adjust for positional and batch effects using ComBat
Adjust for positional and batch effects using ComBat
A fast scatterplot smoother suitable for microarray normalization
A fast scatterplot smoother suitable for microarray normalization
Algorithms for Calculating Microarray Enrichment (ACME)
Algorithms for Calculating Microarray Enrichment (ACME)
alpine
alpine
alpine
A mass spectrometry imaging toolbox for statistical analysis
A mass spectrometry imaging toolbox for statistical analysis
Analysing Illumina HumanMethylation BeadChip Data
Analysing Illumina HumanMethylation BeadChip 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 high-throughput gene perturbation screens
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 integrated analysis package of miRNA and mRNA expression data
A Normalization and Copy Number Variation Detection Method for Whole Exome Sequencing
A Normalization and Copy Number Variation Detection Method for Whole Exome Sequencing
A normalization method for Copy Number Aberration in cancer samples
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 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 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
An R package of Data Importing, Processing and Analysis for Opera High Content Screening System
A test for when to use quantile normalization
A test for when to use quantile normalization
A test for when to use quantile normalization
AUCell: Analysis of 'gene set' activity in single-cell RNA-seq data (e.g. identify cells with specific gene signatures)
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 Analysis with Windows
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
Compensates for the bias introduced by median normalization in phosphoproteomics
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 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
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
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
Differential Analyis of Hi-C Data
Differential Analyis of Hi-C Data
Differential Analyis of Hi-C Data
Differential Binding Estimation for Protein Complexes
Differential Expression Analysis of NanoString nCounter Data
Differential Expression Analysis of NanoString nCounter Data
Empirical Analysis of Digital Gene Expression Data in R
Empirical Analysis of Digital Gene Expression Data in R
Enhanced copy-number variation analysis using Illumina DNA methylation arrays
Enhanced copy-number variation analysis using Illumina DNA methylation arrays
Experimental Design in Differential Abundance analysis
Experimental Design in Differential Abundance analysis
Fast Methylome-Wide Association Study Pipeline for Enrichment Platforms
Fast Methylome-Wide Association Study Pipeline for Enrichment Platforms
Fast Methylome-Wide Association Study Pipeline for Enrichment Platforms
Feature Specific Quantile Normalization
Filter replicated high-throughput transcriptome sequencing data
Filter replicated high-throughput transcriptome sequencing data
GUI for limma package with Affymetrix microarrays
GUI for limma package with Affymetrix microarrays
GUI for limma package with two color 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
Infers biological signatures from gene expression data
Infers biological signatures from gene expression data
Intron-Exon Retention Estimator
Intron-Exon Retention Estimator
Intron-Exon Retention Estimator
IP-seq data analysis and vizualization
IP-seq data analysis and vizualization
IP-seq data analysis and vizualization
Linear model and normality based transformation method (Linnorm)
Linear model and normality based transformation method (Linnorm)
Linear Models for Microarray Data
Linear Models for Microarray Data
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
MetCleaning
Methods for Single-Cell RNA-Seq Data Analysis
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
Normalization and difference calling in ChIP-seq data
Normalization and difference calling in ChIP-seq data
Normalization and difference calling in ChIP-seq 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
Normalization Procedure for Infinium HumanMethylation450 BeadChip Kit
peakAnnotation
Permutation-Based Confidence for Molecular Classification
Permutation-Based Confidence for Molecular Classification
Preprocessing of Illumina Infinium 450K data
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 Control for Single-Cell RNA-seq Data
Quality metrics and data processing methods for NanoString mRNA gene expression data
Quality metrics and data processing methods for NanoString mRNA gene expression data
Rcpp Integration Surrogate Variable Analysis
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
Removal of unwanted variation for gene-gene correlations and related analysis
Repetitive Element Methylation Prediction
Repetitive Element Methylation Prediction
Repetitive Element Methylation Prediction
R Normalization and Inference of Time Series data
R Normalization and Inference of Time Series data
R Normalization and Inference of Time Series data
RUV for normalization of expression array data
RUV for normalization of expression array data
showTags2
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 Overview of Normalized Expression data
Single Cell Overview of Normalized Expression data
Single Cell Overview of Normalized Expression data
Smooth quantile normalization
Smooth quantile normalization
Statistical analysis for sparse high-throughput sequencing
Statistical analysis for sparse high-throughput sequencing
Statistical analysis for sparse high-throughput sequencing
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
Suite of Functions for Pooled Crispr Screen QC and Analysis
Surrogate Variable Analysis
Surrogate Variable Analysis
Surrogate Variable Analysis
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 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
The removal of batch effects from datasets using a PCA and constrained optimisation based technique
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
Tools for the preprocessing and analysis of the Illumina microarrays on the detector (bead) level
YARN: Robust Multi-Condition RNA-Seq Preprocessing and Normalization
YARN: Robust Multi-Condition RNA-Seq Preprocessing and Normalization
YARN: Robust Multi-Condition RNA-Seq Preprocessing and Normalization