Loading, transforming and summarizing

Functions to load data, add covariates or annotations, or provide high-level summaries.

FromFlatDF() FluidigmAssay()

Construct a SingleCellAssay (or derived subclass) from a `flat` (melted) data.frame/data.table

FromMatrix()

Construct a SingleCellAssay from a matrix or array of expression

SceToSingleCellAssay()

Coerce a SingleCellExperiment to some class defined in MAST

convertMASTClassicToSingleCellAssay()

Convert a MASTClassic SingleCellAssay

magic_assay_names() assay(<SingleCellAssay>,<missing>)

Default assay returned

melt(<SingleCellAssay>)

"Melt" a SingleCellAssay matrix

zlm()

Zero-inflated regression for SingleCellAssay

freq() condmean() condSd() numexp()

Summary statistics for genes in an experiment

getConcordance() getwss() getss() getrc()

Get the concordance between two experiments

read.fluidigm()

Reads a Fluidigm Biomark (c. 2011) raw data file (or set of files)

primerAverage()

Average expression values for duplicated/redundant genes

mast_filter() burdenOfFiltering()

Filter a SingleCellAssay

Thresholding

Adaptive thresholding of background noise.

thresholdSCRNACountMatrix()

Threshold a count matrix using an adaptive threshold.

summary(<thresholdSCRNACountMatrix>) print(<summaryThresholdSCRNA>)

Summarize the effect of thresholding

plot(<thresholdSCRNACountMatrix>)

Plot cutpoints and densities for thresholding

Differential Expression Testing with Hurdle Model

Fit a Hurdle linear model to test for zero-inflated differential expression.

zlm()

Zero-inflated regression for SingleCellAssay

update(<LMERlike>) vcov(<LMERlike>) coef(<LMERlike>) logLik(<LMERlike>)

Wrapper for lmer/glmer

BayesGLMlike-class

Wrapper for bayesian GLM

print(<summaryZlmFit>)

Print summary of a ZlmFit

ebayes()

Estimate hyperparameters for hierarchical variance model for continuous component

defaultPrior()

Initialize a prior to be used a prior for BayeGLMlike/BayesGLMlike2

Specifying hypothesis and contrasts to test

Testing linear functions of coefficients.

Hypothesis()

Describe a linear model hypothesis to be tested

lrTest()

Run a likelihood-ratio test

waldTest()

Run a Wald test

Low-level manipulation of fitted hurdle models

Return coefficients, standard errors, etc. Calculate and return residuals from models.

BayesGLMlike-class

Wrapper for bayesian GLM

CovFromBoots()

Extract the intere-gene covariance matrices for continuous and discrete components of a MAST model for a given coefficient from bootstrap replicates

Drop()

Drop specified dimension from an array

FromFlatDF() FluidigmAssay()

Construct a SingleCellAssay (or derived subclass) from a `flat` (melted) data.frame/data.table

FromMatrix()

Construct a SingleCellAssay from a matrix or array of expression

vcov(<GLMlike>)

Wrapper for regular glm/lm

GSEATests-class

An S4 class for Gene Set Enrichment output

Hypothesis()

Describe a linear model hypothesis to be tested

update(<LMERlike>) vcov(<LMERlike>) coef(<LMERlike>) logLik(<LMERlike>)

Wrapper for lmer/glmer

summary(<LMlike>) update(<LMlike>) waldTest(<LMlike>,<CoefficientHypothesis>) waldTest(<LMlike>,<matrix>) lrTest(<LMlike>,<character>) lrTest(<LMlike>,<CoefficientHypothesis>) lrTest(<LMlike>,<Hypothesis>) lrTest(<LMlike>,<matrix>) logLik(<GLMlike>)

Linear Model-like Class

LRT()

Likelihood Ratio Tests for SingleCellAssays

MAST-package

MAST: Model-based Analysis of Single- cell Transcriptomics

SceToSingleCellAssay()

Coerce a SingleCellExperiment to some class defined in MAST

lrTest(<ZlmFit>,<CoefficientHypothesis>) lrTest(<ZlmFit>,<Hypothesis>) lrTest(<ZlmFit>,<matrix>) waldTest(<ZlmFit>,<CoefficientHypothesis>) waldTest(<ZlmFit>,<Hypothesis>) coef(<ZlmFit>) vcov(<ZlmFit>) se.coef(<ZlmFit>)

An S4 class to hold the output of a call to zlm

applyFlat()

Apply a vectorized binary operation recycling over last dimension

bootVcov1()

Bootstrap a zlmfit

cData() `cData<-`() combine(<SingleCellAssay>,<SingleCellAssay>) combine(<SingleCellAssay>,<ANY>)

Deprecated cell/feature data accessors/mutators

calcZ()

Get Z or T statistics and P values after running gseaAfterBoot

`colData<-`(<SingleCellAssay>,<DataFrame>)

Replace colData

collectResiduals() discrete_residuals_hook() continuous_residuals_hook() combined_residuals_hook() deviance_residuals_hook() fitted_phat() partialScore()

Residual hooks and collection methods

computeEtFromCt()

Compute the Et from the Ct

convertMASTClassicToSingleCellAssay()

Convert a MASTClassic SingleCellAssay

magic_assay_names() assay(<SingleCellAssay>,<missing>)

Default assay returned

defaultPrior()

Initialize a prior to be used a prior for BayeGLMlike/BayesGLMlike2

dof()

Degrees of freedom of Zero inflated model

ebayes()

Estimate hyperparameters for hierarchical variance model for continuous component

expavg()

Exponential average

fData

fData

featureData

Accessor for featureData AnnotatedDataFrame

filterLowExpressedGenes()

Filter low-expressing genes

fit()

fit a zero-inflated regression

freq() condmean() condSd() numexp()

Summary statistics for genes in an experiment

getConcordance() getwss() getss() getrc()

Get the concordance between two experiments

getwellKey()

Accessor for wellKey

gseaAfterBoot() gsea_control()

Gene set analysis for hurdle model

hushWarning()

Selectively muffle warnings based on output

impute()

impute missing continuous expression for plotting

influence(<bayesglm>)

Influence bayesglm object

invlogit()

Inverse of logistic transformation

logFC() getLogFC()

Calculate log-fold changes from hurdle model components

logmean()

Log mean

lrTest(<ZlmFit>,<character>)

Likelihood ratio test

lrTest()

Run a likelihood-ratio test

maits

MAITs data set, RNASeq

mast_filter() burdenOfFiltering()

Filter a SingleCellAssay

melt(<SingleCellAssay>)

"Melt" a SingleCellAssay matrix

`model.matrix<-`()

Replace model matrix

model.matrix()

Model matrix accessor

myBiplot()

Makes a nice BiPlot

pbootVcov1()

Bootstrap a zlmfit

plot(<thresholdSCRNACountMatrix>)

Plot cutpoints and densities for thresholding

plotSCAConcordance()

Concordance plots of filtered single vs n-cell assays

plotlrt()

Plot a likelihood ratio test object

predict(<ZlmFit>)

Return predictions from a ZlmFit object.

predicted_sig

Predicted signatures

primerAverage()

Average expression values for duplicated/redundant genes

print(<summaryZlmFit>)

Print summary of a ZlmFit

read.fluidigm()

Reads a Fluidigm Biomark (c. 2011) raw data file (or set of files)

removeResponse()

Remove the left hand side (response) from a formula

rstandard(<bayesglm>)

rstandard for bayesglm objects.

se.coef()

Return coefficient standard errors

show(<LMlike>) show(<ZlmFit>)

show

split(<SingleCellAssay>,<character>)

Split into list

stat_ell()

Plot confidence ellipse in 2D

subset(<SingleCellAssay>)

Subset a SingleCellAssay by cells (columns)

summarize()

Return programmatically useful summary of a fit

summary(<GSEATests>)

Summarize gene set enrichment tests

summary(<ZlmFit>)

Summarize model features from a ZlmFit object

summary(<thresholdSCRNACountMatrix>) print(<summaryThresholdSCRNA>)

Summarize the effect of thresholding

thresholdSCRNACountMatrix()

Threshold a count matrix using an adaptive threshold.

vbeta

Vbeta Data Set

vbetaFA

Vbeta Data Set, FluidigmAssay

waldTest(<ZlmFit>,<matrix>)

Wald test

waldTest()

Run a Wald test

xform()

Make matrix of continuous expression values, orthogonal to discrete

zlm()

Zero-inflated regression for SingleCellAssay

Gene set enrichment testing

Tests on the average differential expression effect in a gene set, accounting for gene-gene correlations. Uses bootstraps to assess the gene-gene correlations.

gseaAfterBoot() gsea_control()

Gene set analysis for hurdle model

bootVcov1()

Bootstrap a zlmfit

pbootVcov1()

Bootstrap a zlmfit

summary(<GSEATests>)

Summarize gene set enrichment tests

Plotting methods

Miscellaneous plotting methods. Concordance, PCA biplots, and effects plots for fitted hurdle models.

myBiplot()

Makes a nice BiPlot

plotSCAConcordance()

Concordance plots of filtered single vs n-cell assays

stat_ell()

Plot confidence ellipse in 2D