NxtSE-class: The NxtSE class

In alexchwong/SpliceWiz: interactive analysis and visualization of alternative splicing in R

The NxtSE class

Description

The NxtSE class inherits from the SummarizedExperiment class and is constructed using makeSE. NxtSE extends SummarizedExperiment by housing additional assays pertaining to IR and splice junction counts.

Usage

NxtSE(...)

## S4 method for signature 'NxtSE'
up_inc(x, withDimnames = TRUE, ...)

## S4 method for signature 'NxtSE'
down_inc(x, withDimnames = TRUE, ...)

## S4 method for signature 'NxtSE'
up_exc(x, withDimnames = TRUE, ...)

## S4 method for signature 'NxtSE'
down_exc(x, withDimnames = TRUE, ...)

## S4 method for signature 'NxtSE'
covfile(x, withDimnames = TRUE, ...)

## S4 method for signature 'NxtSE'
sampleQC(x, withDimnames = TRUE, ...)

## S4 method for signature 'NxtSE'
sourcePath(x, withDimnames = TRUE, ...)

## S4 method for signature 'NxtSE'
row_gr(x, withDimnames = TRUE, ...)

## S4 method for signature 'NxtSE'
ref(x, withDimnames = TRUE, ...)

## S4 method for signature 'NxtSE'
junc_PSI(x, withDimnames = TRUE, ...)

## S4 method for signature 'NxtSE'
junc_counts(x, withDimnames = TRUE, ...)

## S4 method for signature 'NxtSE'
junc_counts_uns(x, withDimnames = TRUE, ...)

## S4 method for signature 'NxtSE'
junc_gr(x, withDimnames = TRUE, ...)

## S4 method for signature 'NxtSE'
update_NxtSE(x, ...)

## S4 method for signature 'NxtSE'
realize_NxtSE(x, includeJunctions = FALSE, withDimnames = TRUE, ...)

## S4 replacement method for signature 'NxtSE'
up_inc(x, withDimnames = TRUE) <- value

## S4 replacement method for signature 'NxtSE'
down_inc(x, withDimnames = TRUE) <- value

## S4 replacement method for signature 'NxtSE'
up_exc(x, withDimnames = TRUE) <- value

## S4 replacement method for signature 'NxtSE'
down_exc(x, withDimnames = TRUE) <- value

## S4 replacement method for signature 'NxtSE'
covfile(x, withDimnames = TRUE) <- value

## S4 replacement method for signature 'NxtSE'
sampleQC(x, withDimnames = TRUE) <- value

## S4 method for signature 'NxtSE,ANY,ANY,ANY'
x[i, j, ..., drop = TRUE]

## S4 replacement method for signature 'NxtSE,ANY,ANY,NxtSE'
x[i, j, ...] <- value

## S4 method for signature 'NxtSE'
cbind(..., deparse.level = 1)

## S4 method for signature 'NxtSE'
rbind(..., deparse.level = 1)

Arguments

...	In NxtSE(), additional arguments to be passed onto SummarizedExperiment()
x	A NxtSE object
withDimnames	(default TRUE) Whether exported assays should be supplied with row and column names of the NxtSE object. See SummarizedExperiment
includeJunctions	When realizing a NxtSE object, include whether junction counts and PSIs should be realized into memory. Not recommended for general use, as they are only used for coverage plots.
value	The value to replace. Must be a matrix for the up_inc<-, down_inc<-, up_exc<- and down_exc<- replacers, and a character vector for covfile<-
i, j	Row and column subscripts to subset a NxtSE object.
drop	A logical(1), ignored by these methods.
deparse.level	See base::cbind for a description of this argument.

Value

See Functions section (below) for details

Functions

• NxtSE(): Constructor function for NxtSE; akin to SummarizedExperiment(...)

• up_inc(NxtSE): Gets upstream included events (SE/MXE), or upstream exon-intron spanning reads (IR)

• down_inc(NxtSE): Gets downstream included events (SE/MXE), or downstream exon-intron spanning reads (IR)

• up_exc(NxtSE): Gets upstream excluded events (MXE only)

• down_exc(NxtSE): Gets downstream excluded events (MXE only)

• covfile(NxtSE): Gets a named vector with the paths to the corresponding COV files

• sampleQC(NxtSE): Gets a data frame with the QC parameters of the samples

• sourcePath(NxtSE): Retrieves the directory path containing the source data for this NxtSE object.

• row_gr(NxtSE): Retrieves a GRanges object representing the genomic spans of the ASEs (EventRegion as GRanges)

• ref(NxtSE): Retrieves a list of annotation data associated with this NxtSE object; primarily used in plotCoverage()

• junc_PSI(NxtSE): Getter for junction PSI DelayedMatrix; primarily used in plotCoverage()

• junc_counts(NxtSE): Getter for junction counts DelayedMatrix; primarily used in plotCoverage()

• junc_counts_uns(NxtSE): Getter for (unstranded) junction counts DelayedMatrix; primarily used in plotCoverage()

• junc_gr(NxtSE): Getter for junction GenomicRanges coordinates; primarily used in plotCoverage()

• update_NxtSE(NxtSE): Updates NxtSE object to the latest version.

• realize_NxtSE(NxtSE): Converts all DelayedMatrix assays as matrices (i.e. performs all delayed calculation and loads resulting object to RAM)

• up_inc(NxtSE) <- value: Sets upstream included events (SE/MXE), or upstream exon-intron spanning reads (IR)

• down_inc(NxtSE) <- value: Sets downstream included events (SE/MXE), or downstream exon-intron spanning reads (IR)

• up_exc(NxtSE) <- value: Sets upstream excluded events (MXE only)

• down_exc(NxtSE) <- value: Sets downstream excluded events (MXE only)

• covfile(NxtSE) <- value: Sets the paths to the corresponding COV files

• sampleQC(NxtSE) <- value: Sets the values in the data frame containing sample QC

• x[i: Subsets a NxtSE object

• `[`(x = NxtSE, i = ANY, j = ANY) <- value: Sets a subsetted NxtSE object

• cbind(NxtSE): Combines two NxtSE objects (by samples - columns)

• rbind(NxtSE): Combines two NxtSE objects (by AS/IR events - rows)

Examples

# Run the full pipeline to generate a NxtSE object:

buildRef(
    reference_path = file.path(tempdir(), "Reference"),
    fasta = chrZ_genome(), 
    gtf = chrZ_gtf()
)

bams <- SpliceWiz_example_bams()
processBAM(bams$path, bams$sample,
  reference_path = file.path(tempdir(), "Reference"),
  output_path = file.path(tempdir(), "SpliceWiz_Output")
)

expr <- findSpliceWizOutput(file.path(tempdir(), "SpliceWiz_Output"))
collateData(expr, 
  reference_path = file.path(tempdir(), "Reference"),
  output_path = file.path(tempdir(), "Collated_output")
)

se <- makeSE(collate_path = file.path(tempdir(), "Collated_output"))

# Coerce NxtSE -> SummarizedExperiment
se_raw <- as(se, "SummarizedExperiment")

# Coerce SummarizedExperiment -> NxtSE
se_NxtSE <- as(se_raw, "NxtSE")
identical(se, se_NxtSE) # Returns TRUE

# Update NxtSE object to the latest version
# - useful if an NxtSE object made with old SpliceWiz version
# - was stored as an RDS obejct

se <- update_NxtSE(se)

# Get directory path of NxtSE (i.e., collate_path)
sourcePath(se)

# Get Main Assay Counts
assay(se, "Included") # Junction (or IR depth) counts for included isoform
assay(se, "Excluded") # Junction (or IR depth) counts for excluded isoform

# Get Auxiliary Counts (for filter use only)
assay(se, "Coverage") # Participation ratio (intron coverage for IR/RI)
assay(se, "minDepth") # SpliceOver junction counts (Intron Depths for IR/RI)
assay(se, "Depth")    # Sum of intron depth and SpliceOver (used for
                      # coverage normalization factor

# Get Junction reads of SE / MXE and spans-reads of IR events
up_inc(se)   # Upstream included junction counts (IR/MXE/SE/RI)
down_inc(se) # Downstream included junction counts (IR/MXE/SE/RI)
up_exc(se)   # Upstream excluded junction counts (MXE only)
down_exc(se) # Downstream excluded junction counts (MXE only)

# Get Junction counts
junc_counts(se) # stranded (if RNA-seq is auto-detected as stranded)
junc_counts_uns(se) # unstranded (sum of junction reads from both strand)
junc_PSI(se) # PSI of junction (as proportion of SpliceOver metric)

# Get Junction GRanges object
junc_gr(se)

# Get EventRegion as GRanges object
row_gr(se)

# Get list of available coverage files
covfile(se)

# Get sample QC information
sampleQC(se)

# Get resource data (used internally for plotCoverage())
cov_data <- ref(se)
names(cov_data)

# Subset functions
se_by_samples <- se[,1:3]
se_by_events <- se[1:10,]
se_by_rowData <- subset(se, EventType == "IR")

# Cbind (bind event_identical NxtSE by samples)
se_by_samples_1 <- se[,1:3]
se_by_samples_2 <- se[,4:6]
se_cbind <- cbind(se_by_samples_1, se_by_samples_2)
identical(se, se_cbind) # should return TRUE

# Rbind (bind sample_identical NxtSE by events)
se_IR <- subset(se, EventType == "IR")
se_SE <- subset(se, EventType == "SE")
se_IRSE <- rbind(se_IR, se_SE)
identical(se_IRSE, subset(se, EventType %in% c("IR", "SE"))) # TRUE

# Convert HDF5-based NxtSE to in-memory se
# makeSE() creates a HDF5-based NxtSE object where all assay data is stored
# as an h5 file instead of in-memory. All operations are performed as
# delayed operations as per DelayedArray package.
# To realize the NxtSE object as an in-memory object, use:

se_real <- realize_NxtSE(se)
identical(se, se_real) # should return FALSE

# To check the difference, run:
class(up_inc(se))
class(up_inc(se_real))

alexchwong/SpliceWiz documentation built on Oct. 15, 2024, 10:12 a.m.