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Fundamentals

Loading data

Functions to read data from files or urls

ClassifyGenes()
Build the type column for the gene info table.
Design
A list of predefined names for design vectors
DesignSemantics()
Build the design semantics list
MakeColdata()
Extract an annotation table from a formatted names vector
ReadGRAND()
Read the output of GRAND-SLAM 2.0 into a grandR object.
ReadGRAND3()
Read the output of GRAND-SLAM 3.0 into a grandR object.
Semantics.time()
Semantics for time columns

Data preprocessing

Functions to preprocess data

ComputeAbsolute()
Compute absolute expression using ERCC spike ins
ComputeNtrPosteriorQuantile() ComputeNtrCI() ComputeNtrPosteriorLower() ComputeNtrPosteriorUpper()
Compute NTR quantiles
FilterGenes()
Filter genes
Normalize() NormalizeFPKM() NormalizeRPM() NormalizeTPM()
Normalization
NormalizeBaseline()
Normalization to a baseline
Scale()
Scale data

Interacting with grandR objects

Retrieve information from grandR objects

Analyses() AddAnalysis() DropAnalysis()
Analysis table functions
Coldata() `Coldata<-`()
Get the column annotation table or add additional columns to it
Condition() `Condition<-`()
Get or set the conditions in the column annotation table.
DefaultSlot() `DefaultSlot<-`()
Get or set the default slot for a grandR object.
GeneInfo() `GeneInfo<-`()
Get the gene annotation table or add additional columns to it
Genes() Columns()
Gene and sample (or cell) names
Plots() AddGenePlot() AddGlobalPlot() PlotGene() PlotGlobal() DropPlots()
Stored plot functions
Slots() DropSlot() AddSlot()
Slot functions
grandR() VersionString() Title() dim(<grandR>) is.grandR() dimnames(<grandR>) print(<grandR>) subset(<grandR>) split(<grandR>) merge(<grandR>)
Create a grandR object and retrieve basic information

Data retrieval

Functions and helper functions to retrieve data from grandR objects

ComputeExpressionPercentage()
Expression percentage computation
GetAnalysisTable()
Obtain a table of analysis results values
GetData()
Obtain a tidy table of values for a gene or a small set of genes
GetSparseMatrix()
Obtain a genes x values table as a sparse matrix
GetSummarizeMatrix()
Create a summarize matrix
GetTable()
Obtain a genes x values table

Analyses

Differential expression

Analyze differential expression (snapshot experiments)

EstimateRegulation()
Estimate regulation from snapshot experiments
GetContrasts()
Create a contrast matrix
GetSignificantGenes()
Significant genes
LFC()
Estimation of log2 fold changes
LikelihoodRatioTest()
Compute a likelihood ratio test.
PairwiseDESeq2()
Perform Wald tests for differential expression

Progressive labeling timecourses

Infer kinetic parameters from progressive labeling timecourses

FitKinetics()
Fit kinetic models to all genes.
FitKineticsGeneLeastSquares()
Fit a kinetic model according to non-linear least squares.
FitKineticsGeneLogSpaceLinear()
Fit a kinetic model using a linear model.
FitKineticsGeneNtr()
Fit a kinetic model using the degradation rate transformed NTR posterior distribution.
FitKineticsPulseR()
Fit kinetics using pulseR
PlotSimulation()
Plot simulated data
SimulateKinetics()
Simulate the kinetics of old and new RNA for given parameters.
f.old.equi() f.old.nonequi() f.new()
Functions to compute the abundance of new or old RNA at time t.

Modeling snapshot data

Infer parameters from snapshot data with or without steady state assumptions

ComputeSteadyStateHalfLives()
Steady state half-lives for each sample
FindReferences()
Obtain reference columns (samples or cells) for all columns (samples or cells) in the data set
FitKineticsGeneSnapshot()
Compute the posterior distributions of RNA synthesis and degradation for a particular gene
FitKineticsSnapshot()
Fits RNA kinetics from snapshot experiments
TransformSnapshot()
Estimate parameters for a one-shot experiment.

Gene set tests

Functions to do GSEA,ORA,etc.

AnalyzeGeneSets()
Gene set analysis
ListGeneSets()
List available gene sets

Visualization

Gene plots

Functions to plot data for a single gene

PlotGeneGroupsBars()
Plot gene values as bars
PlotGeneGroupsPoints()
Plot gene groups as points
PlotGeneOldVsNew()
Gene plot comparing old vs new RNA
PlotGeneProgressiveTimecourse()
Plot progressive labeling timecourses
PlotGeneSnapshotTimecourse()
Gene plot for snapshot timecourse data
PlotGeneTotalVsNtr()
Gene plot comparing total RNA vs the NTR

Global plots

Functions to plot data summarizing the whole data set

FormatCorrelation()
Formatting function for correlations
MAPlot()
Make an MA plot
PlotAnalyses()
Convenience function to make the same type of plot for multple analyses.
PlotHeatmap()
Create heatmaps from grandR objects
PlotPCA()
Make a PCA plot
PlotScatter()
Make a scatter plot
PlotTypeDistribution()
Plot the distribution of gene types
Transform.no() Transform.Z() Transform.VST() Transform.logFC()
Transformations for PlotHeatmap
VulcanoPlot()
Make a Vulcano plot

Web interface

Functions related to the shiny web-interface

ServeGrandR()
Serve a shiny web interface

QC

Toxicity checks

Functions to check for 4sU toxicity

Temporal recalibration

Functions for recalibration of labeling times (to get effective labeling from nominal labeling times)

CalibrateEffectiveLabelingTimeKineticFit()
Uses the kinetic model to calibrate the effective labeling time.
CalibrateEffectiveLabelingTimeMatchHalflives()
Calibrate the effective labeling time by matching half-lives to a .reference

GRAND3 quality control plots

Generate quality control plot from the statistics generated by GRAND3

GetDiagnosticParameters()
Describe parameters relevant to diagnostics
PlotConversionFreq()
Diagnostic plot for conversion frequencies
PlotMismatchPositionForSample()
Diagnostic plot for mismatch position for columns (by sample)
PlotMismatchPositionForType()
Diagnostic plot for mismatch position for columns (by mismatch type)
PlotModelCompareConv()
Diagnostic plot for estimated models (global conversion rate)
PlotModelCompareErr()
Diagnostic plot for estimated models (global error rate)
PlotModelCompareErrPrior()
Diagnostic plot for estimated models (global error rate)
PlotModelCompareLL()
Diagnostic plot for estimated models (log likelihoods)
PlotModelCompareNtr()
Diagnostic plot for estimated models (global NTR)
PlotModelConv()
Diagnostic plot for estimated models (global conversion rate)
PlotModelErr()
Diagnostic plot for estimated models (global error rate)
PlotModelLabelTimeCourse()
Diagnostic plot for estimated models (4sU increase)
PlotModelNtr()
Diagnostic plot for estimated models (global NTR)
PlotModelShape()
Diagnostic plot for estimated models (global shape parameter)
PlotProfileLikelihood()
Diagnostic plot for estimated models (global error rate)

Misc

Read simulation

Functions for in-silico simulation of nucleotide conversion data

SimulateReadsForSample()
Simulate metabolic labeling - nucleotide conversion RNA-seq data.
SimulateTimeCourse()
Simulate a complete time course of metabolic labeling - nucleotide conversion RNA-seq data.

Helper functions

ApplyContrasts()
Apply a function over contrasts
Defer()
Defer calling a function
IsParallel()
Checks for parallel execution
RotatateAxisLabels()
Rotate x axis labels
SetParallel()
Set up parallel execution
ToIndex()
Obtain the indices of the given genes
check.analysis() check.slot() check.mode.slot()
Internal functions to check for a valid analysis or slot names.
data.apply()
Internal function to apply functions to all slots etc.
density2d()
Density estimation in 2d
estimate.dispersion()
Estimate dispersion parameters for a count matrix using DESeq2
get.mode.slot()
Internal functions to parse mode.slot strings
psapply() plapply()
Parallel (s/l)apply
structure2vector() kinetics2vector()
Convert a structure into a vector