IsoformSwitchTestDEXSeq: Statistical Test for identifying Isoform Switching via DEXSeq

Description Usage Arguments Details Value Author(s) References See Also Examples

Description

This function utilizes DEXSeq to test isoforms (isoform resolution) for differential isoform usage. It can furthermore also estimate corrected effect sizes (IF and dIF) in experimental setups with confounding effects (such as batches).

Usage

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isoformSwitchTestDEXSeq(
    ### Core arguments
    switchAnalyzeRlist,
    alpha = 0.05,
    dIFcutoff = 0.1,

    ### Advanced arguments
    correctForConfoundingFactors=TRUE,
    overwriteIFvalues=TRUE,
    reduceToSwitchingGenes = TRUE,
    reduceFurtherToGenesWithConsequencePotential = TRUE,
    onlySigIsoforms = FALSE,
    keepIsoformInAllConditions = TRUE,
    showProgress = TRUE,
    quiet = FALSE
)

Arguments

switchAnalyzeRlist

A switchAnalyzeRlist object.

alpha

The cutoff which the FDR correct p-values must be smaller than for calling significant switches. Default is 0.05.

dIFcutoff

The cutoff which the changes in (absolute) isoform usage must be larger than before an isoform is considered switching. This cutoff can remove cases where isoforms with (very) low dIF values are deemed significant and thereby included in the downstream analysis. This cutoff is analogous to having a cutoff on log2 fold change in a normal differential expression analysis of genes to ensure the genes have a certain effect size. Default is 0.1 (10%).

correctForConfoundingFactors

A logic indicating whether IsoformSwitchAnalyzeR to use limma to correct for any confounding effects (e.g. batch effects) as indicated in the design matrix (as additional columns (apart from the two default columns)). Default is TRUE.

overwriteIFvalues

A logic indicating whether to overwrite the IF and dIF stored in the switchAnalyzeRlist with the corrected IF and dIF values - if no confounding effects are present in the design matrix this will not change anything. Default is TRUE.

reduceToSwitchingGenes

A logic indicating whether the switchAnalyzeRlist should be reduced to the genes which contains at least one isoform significantly differential used (as indicated by the alpha and dIFcutoff parameters) - works on dIF values corrected for confounding effects if overwriteIFvalues=TRUE. Enabling this will make the downstream analysis a lot faster since fewer genes needs to be analyzed. Default is TRUE.

reduceFurtherToGenesWithConsequencePotential

A logic indicating whether the switchAnalyzeRlist should be reduced to the genes which have the potential to find isoform switches with predicted consequences. This argument is a more strict version of reduceToSwitchingGenes as it not only requires that at least one isoform is significantly differential used (as indicated by the alpha and dIFcutoff parameters) but also that there is an isoform with the opposite effect size (e.g. used less if the first isoform is used more). The minimum effect size of the opposing isoform usage is also controlled by dIFcutoff. The existence of such an opposing isoform means a switch pair can be formed. It is these pairs that can be analyzed for functional consequences further downstream in the IsoformSwitchAnalyzeR workflow. Enabling this will make the downstream analysis a even faster (than just using reduceToSwitchingGenes) since fewer genes needs to be analyzed. Requires that reduceToSwitchingGenes=TRUE to have any effect. Default is TRUE.

onlySigIsoforms

A logic indicating whether both isoforms the pairs considered if reduceFurtherToGenesWithConsequencePotential=TRUE should be significantly differential used (as indicated by the alpha and dIFcutoff parameters). Default is FALSE (aka only one of the isoforms in a pair should be significantly differential used).

keepIsoformInAllConditions

A logic indicating whether the an isoform should be kept in all comparisons even if it is only deemed significant (as defined by the alpha and dIFcutoff parameters) in one comparison. This will not affect downstream runtimes only make the switchAnalyzeRlist use slightly more memmory (scaling with the number of conditions compared). Default is TRUE.

showProgress

A logic indicating whether to make a progress bar (if TRUE) or not (if FALSE). Defaults is FALSE.

quiet

A logic indicating whether to avoid printing progress messages (incl. progress bar). Default is FALSE

Details

This function uses DEXSeq to test for differential isoform usage using the replicate count matrix. This is done by for each pairwise comparison building and testing one model (building one combined model and testing each pairwise comparison from that is not supported by DEXSeq).

isoformSwitchTestDEXSeq also allows for estimation of effect sizes (IF and dIF) corrected for confounding effects (controlled by correctForConfoundingFactors = TRUE) (recommended). Confounding effects (stored as additional column(s) in the design matrix ( switchAnalyzeRlist$designMatrix )) is done by by performing a batch correction on the isoform abundance matrix with limma::removeBatchEffect() and afterwards recalculate the IF matrix and summarize the IF and dIF values. These new estimates can be added to the switchAnalyzeRlist (overwriting the existing values) by setting overwriteIFvalues = TRUE.

Note that the actual testing via DEXSeq always will take confounding effects into account (a full model including all confounding effects are always made).

Value

A switchAnalyzeRlist where the following have been modified:

The data.frame added have one row per isoform per comparison of condition and contains the following columns:

Author(s)

Kristoffer Vitting-Seerup

References

Vitting-Seerup et al. The Landscape of Isoform Switches in Human Cancers. Mol. Cancer Res. (2017). Anders et al. Detecting differential usage of exons from RNA-seq data. Genome Research (2012).

See Also

preFilter
extractSwitchSummary
extractTopSwitches

Examples

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### Please note
# 1) The way of importing files in the following example with
#       "system.file('pathToFile', package="IsoformSwitchAnalyzeR") is
#       specialized way of accessing the example data in the IsoformSwitchAnalyzeR package
#       and not something you need to do - just supply the string e.g.
#       "myAnnotation/isoformsQuantified.gtf" to the functions
# 2) importRdata directly supports import of a GTF file - just supply the
#       path (e.g. "myAnnotation/isoformsQuantified.gtf") to the isoformExonAnnoation argument

### Import quantifications
salmonQuant <- importIsoformExpression(system.file("extdata/", package="IsoformSwitchAnalyzeR"))

### Make design matrix
myDesign <- data.frame(
    sampleID = colnames(salmonQuant$abundance)[-1],
    condition = gsub('_.*', '', colnames(salmonQuant$abundance)[-1])
)

### Create switchAnalyzeRlist
aSwitchList <- importRdata(
    isoformCountMatrix   = salmonQuant$counts,
    isoformRepExpression = salmonQuant$abundance,
    designMatrix         = myDesign,
    isoformExonAnnoation = system.file("extdata/example.gtf.gz", package="IsoformSwitchAnalyzeR"),
    showProgress = FALSE
)

### Remove lowly expressed
aSwitchListAnalyzed <- preFilter(aSwitchList)

### Test isoform swtiches
aSwitchListAnalyzed <- isoformSwitchTestDEXSeq(
    switchAnalyzeRlist = aSwitchListAnalyzed
)

# extract summary of number of switching features
extractSwitchSummary(aSwitchListAnalyzed)

kvittingseerup/IsoformSwitchAnalyzeR documentation built on May 12, 2021, 12:25 p.m.