Package: MAnorm2 1.2.2

MAnorm2: Tools for Normalizing and Comparing ChIP-seq Samples

Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) is the premier technology for profiling genome-wide localization of chromatin-binding proteins, including transcription factors and histones with various modifications. This package provides a robust method for normalizing ChIP-seq signals across individual samples or groups of samples. It also designs a self-contained system of statistical models for calling differential ChIP-seq signals between two or more biological conditions as well as for calling hypervariable ChIP-seq signals across samples. Refer to Tu et al. (2021) <doi:10.1101/gr.262675.120> and Chen et al. (2022) <doi:10.1186/s13059-022-02627-9> for associated statistical details.

Authors:Shiqi Tu [aut, cre]

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NEWS

# Install 'MAnorm2' in R:
install.packages('MAnorm2', repos = c('https://tushiqi.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/tushiqi/manorm2/issues

Datasets:
  • H3K27Ac - ChIP-seq Samples for H3K27Ac in Human Lymphoblastoid Cell Lines

On CRAN:

chip-seqdifferential-analysisempirical-bayeswinsorize-values

41 exports 32 stars 2.61 score 15 dependencies 1 mentions 19 scripts 276 downloads

Last updated 2 years agofrom:5fd6bdb1a1. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKAug 24 2024
R-4.5-winOKAug 24 2024
R-4.5-linuxOKAug 24 2024
R-4.4-winOKAug 24 2024
R-4.4-macOKAug 24 2024
R-4.3-winOKAug 24 2024
R-4.3-macOKAug 24 2024

Exports:aovBioCondbioCondcmbBioConddiffTestdiffTest.bioConddistBioCondestimatePriorDfestimatePriorDfRobustestimateSizeFactorsestimateVarRatioestParamHyperChIPextendMeanVarCurvefitMeanVarCurveinv.trigammaisSymPosDefMAplotMAplot.bioCondMAplot.defaultMAplot.diffBioCondmean_var_logwinfnormalizenormalizeBySizeFactorsnormBioCondnormBioCondBySizeFactorsplot.aovBioCondplot.matrixplot.varTestBioCondplotMeanVarCurveplotMVCprint.bioCondprint.summaryBioCondsetMeanVarCurvesetPriorDfsetPriorDfRobustsetPriorDfVarRatiosetWeightsummary.bioCondutil.trigammavarRatiovarTestBioCondvstBioCond

Dependencies:clicolorspacefarvergluelabelinglatticelifecyclelocfitmunsellR6RColorBrewerrlangscalesstatmodviridisLite

MAnorm2 for Normalizing and Comparing ChIP-seq Samples

Shiqi Tu

Rendered fromMAnorm2_vignette.Rmdusingknitr::rmarkdownon Aug 24 2024.

Last update: 2022-10-31
Started: 2020-01-09

Readme and manuals

Help Manual

Help pageTopics
Perform a Moderated Analysis of Variance on 'bioCond' ObjectsaovBioCond
Create a 'bioCond' Object to Group ChIP-seq SamplesbioCond
Check the Regularity of a Count TablecheckCountTable
Check the Validity of an Index VectorcheckIndex
Combine a Set of 'bioCond' Objects into a Single 'bioCond'cmbBioCond
Generic Differential TestdiffTest diffTest.bioCond
Quantify the Distance between Each Pair of Samples in a 'bioCond'distBioCond
Workhorse Function for Estimating Number of Prior Degrees of FreedomestimateD0
Estimate Number of Prior Degrees of Freedom in a Robust MannerestimateD0Robust
Assess the Goodness of Fit of Mean-Variance CurvesestimatePriorDf
Assess the Goodness of Fit of Mean-Variance Curves in a Robust MannerestimatePriorDfRobust
Estimate Size Factors of ChIP-seq SamplesestimateSizeFactors
Estimate Relative Variance Ratio Factors of 'bioCond' ObjectsestimateVarRatio
The Parameter Estimation Framework of HyperChIPestParamHyperChIP
Extend the Application Scope of a Mean-Variance CurveextendMeanVarCurve
Fit a Mean-Variance CurvefitMeanVarCurve
ChIP-seq Samples for H3K27Ac in Human Lymphoblastoid Cell LinesH3K27Ac
Deduce the Sample Mean Signal IntensityintervalMeans
Sample Variance of Replicated Signal IntensitiesintervalVars
Inversion of Trigamma Functioninv.trigamma
Is a Real Matrix Symmetric and Positive Definite?isSymPosDef
Deduce Pearson Correlation Coefficient between M & A ValuesMA.pcc
MAnorm2: a Package for Normalizing and Comparing ChIP-seq SamplesMAnorm2
Generic MA PlottingMAplot MAplot.default
Create an MA Plot on Two 'bioCond' ObjectsMAplot.bioCond
Create an MA Plot on Results of Comparing Two 'bioCond' ObjectsMAplot.diffBioCond
Expectation and Variance of Log Winsorized _F_ Distributionmean_var_logwinf
Fit Mean-Variance Trend by Local RegressionmeanVarLocalFit
Parametrically Fit a Mean-Variance CurvemeanVarParaFit
Create a New Unique ID for a Mean-Variance CurvemvcID.new
Perform MA Normalization on a Set of ChIP-seq Samplesnormalize
Normalize ChIP-seq Samples by Their Size FactorsnormalizeBySizeFactors
Perform MA Normalization on a Set of 'bioCond' ObjectsnormBioCond
Normalize 'bioCond' Objects by Their Size FactorsnormBioCondBySizeFactors
Deduce MA Normalization CoefficientsnormCoef
Plot an 'aovBioCond' Objectplot.aovBioCond
Visualize a Matrix of Numeric Valuesplot.matrix
Plot a 'varTestBioCond' Objectplot.varTestBioCond
Plot a Mean-Variance CurveplotMeanVarCurve
Plot a Mean-Variance Curve on a Single 'bioCond' ObjectplotMVC
Print a 'bioCond' Objectprint.bioCond
Print a 'summaryBioCond' Objectprint.summaryBioCond
Scale a Mean-Variance CurvescaleMeanVarCurve
Scale a Mean-Variance Curve in a Robust MannerscaleMeanVarCurveRobust
Set the Mean-Variance Curve of a Set of 'bioCond' ObjectssetMeanVarCurve
Set the Number of Prior Degrees of Freedom of Mean-Variance CurvessetPriorDf
The Robust Counterpart of 'setPriorDf'setPriorDfRobust
Set the Number of Prior Degrees of Freedom and Variance Ratio FactorssetPriorDfVarRatio
Set the Weights of Signal Intensities Contained in a 'bioCond'setWeight
Summarize a 'bioCond' Objectsummary.bioCond
Utility Trigamma Functionutil.trigamma
Compare Variance Ratio Factors of Two 'bioCond' ObjectsvarRatio
Call Hypervariable and Invariant Intervals for a 'bioCond'varTestBioCond
Apply a Variance-Stabilizing Transformation to a 'bioCond'vstBioCond