Package: MPRAnalyze 1.25.0

Tal Ashuach

MPRAnalyze: Statistical Analysis of MPRA data

MPRAnalyze provides statistical framework for the analysis of data generated by Massively Parallel Reporter Assays (MPRAs), used to directly measure enhancer activity. MPRAnalyze can be used for quantification of enhancer activity, classification of active enhancers and comparative analyses of enhancer activity between conditions. MPRAnalyze construct a nested pair of generalized linear models (GLMs) to relate the DNA and RNA observations, easily adjustable to various experimental designs and conditions, and provides a set of rigorous statistical testig schemes.

Authors:Tal Ashuach [aut, cre], David S Fischer [aut], Anat Kriemer [ctb], Fabian J Theis [ctb], Nir Yosef [ctb],

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MPRAnalyze.pdf |MPRAnalyze.html✨
MPRAnalyze/json (API)
NEWS

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

Peer review:

Bug tracker:https://github.com/yoseflab/mpranalyze/issues

Datasets:

On BioConductor:MPRAnalyze-1.23.0(bioc 3.20)MPRAnalyze-1.22.0(bioc 3.19)

immunooncologysoftwarestatisticalmethodsequencinggeneexpressioncellbiologycellbasedassaysdifferentialexpressionexperimentaldesignclassification

6.82 score 11 stars 30 scripts 192 downloads 5 mentions 26 exports 46 dependencies

Last updated 23 days agofrom:a9ca154b95. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 30 2024
R-4.5-winOKOct 31 2024
R-4.5-linuxOKOct 30 2024
R-4.4-winOKOct 31 2024
R-4.4-macOKOct 31 2024
R-4.3-winOKOct 31 2024
R-4.3-macOKOct 31 2024

Exports:analyzeComparativeanalyzeQuantificationcontrolsdnaAnnotdnaCountsdnaDepthestimateDepthFactorsgetAlphagetDistrParam_DNAgetDistrParam_RNAgetFits_DNAgetFits_RNAgetModelParameters_DNAgetModelParameters_RNAmodelMpraObjectrnaAnnotrnaCountsrnaDepthrowAnnotsetDepthFactorssetModelsimulateMPRAtestCoefficienttestEmpiricaltestLrt

Dependencies:abindaskpassBHBiobaseBiocGenericsBiocParallelclicodetoolscpp11crayoncurlDelayedArrayformatRfutile.loggerfutile.optionsGenomeInfoDbGenomeInfoDbDataGenomicRangesgluehmshttrIRangesjsonlitelambda.rlatticelifecycleMatrixMatrixGenericsmatrixStatsmimeopensslpkgconfigprettyunitsprogressR6rlangS4ArraysS4VectorssnowSparseArraySummarizedExperimentsysUCSC.utilsvctrsXVectorzlibbioc

Analyzing MPRA data with MPRAnalyze

Tal Ashuach

Rendered fromvignette.Rmdusingknitr::rmarkdownon Oct 30 2024.

Last update: 2020-08-21
Started: 2018-05-13

Readme and manuals

Help Manual

Help pageTopics
Run a comparative analysis between conditionsanalyzeComparative
Perform quantitative analysis on the MPRA data. This analysis aims to determine which sequences have a regulatory function, when no condition is being tested.analyzeQuantification
Sample MPRA datace.colAnnot ce.control ce.dnaCounts ce.rnaCounts ChrEpi
estimate library size correction factorsestimateDepthFactors
return the fitted value for the transcription rate.getAlpha
Get model distribution parameters from an MpraObject of a given candidate enhancergetDistrParam_DNA getDistrParam_RNA
Get DNA model-based estimates from an MpraObject (the expected values based on the model). These can be compared with the observed counts to assess goodness of fit.getFits_DNA
Get RNA model-based estimates from an MpraObject (the expected values based on the model). These can be compared with the observed counts to assess goodness of fit.getFits_RNA
extract the DNA model parametersextractModelParameters_DNA extractModelParameters_RNA getModelParameters_DNA getModelParameters_RNA
MpraObjectcontrols controls,MpraObject-method dnaAnnot dnaAnnot,MpraObject-method dnaCounts dnaCounts,MpraObject-method dnaDepth dnaDepth,MpraObject-method model model,MpraObject-method MpraObject MpraObject,matrix-method MpraObject,SummarizedExperiment-method rnaAnnot rnaAnnot,MpraObject-method rnaCounts rnaCounts,MpraObject-method rnaDepth rnaDepth,MpraObject-method rowAnnot rowAnnot,MpraObject-method
Manually set library depth correction factorssetDepthFactors
Set the distributional model used. Default is gamma.pois, and is recommended. Other supoprted models are ln.nb in which the DNA follows a log-normal distribution and the RNA follows a negative binomial, and ln.ln in which both follow log-normal distributions. To use alternative distributional models, use this function before fitting the model.setModel
Simulate an MPRA datasetsimulateMPRA
Calculate the significance of a factor in the regression modeltestCoefficient
test for significant activity (quantitative analysis) using various empirical tests (see details)testEmpirical
Calculate likelihood ratio test for the specific nested modeltestLrt