applyOverlap: Apply function over counts
In IntEREst: Intron-Exon Retention Estimator

Description Usage Arguments Value Author(s) See Also Examples

Runs a function on columns of the counts (assay) of a 'SummarizedExperiment' object (resulted by interest(), interest.sequential() or readInterestResults() ) based on the overalp of its exon/intron coordinates with those of another 'SummarizedExperiment' object. The number of the rows and the dimensions of the counts of the result are equal to those of the subject. The function is applied on the query based on it's overlap to the subject.

applyOverlap(
	query,
	subject,
	type="any",
	replaceValues=FALSE,
	intExCol="int_ex", 
	intronExon="intron",
	sujectGeneNamesCol,
	repeatsTableToFilter=c(),
	scaleFragment=TRUE,
	scaleLength=TRUE,
	unmapValue=0,
	FUN=mean,
	...
)

`query, subject`	SummarizedExperiment objects resulted by `interest()`, `interest.sequential()` or `readInterestResults()` functions.
`type`	The type of overlap. By default it considers any overlap. See findOverlaps-methods for more info.
`replaceValues`	Whether return a 'SummarizedExperiment' object with new counts (resulted by running function) replaced.
`intExCol`	Column name (or number) in the rowData of the objects that represents whether each row of the assay is "intron" or "exon".
`intronExon`	Should be assigned either `'intron'` or `'exon'` or `c('intron','exon')` based on whether match the PWM to the intronic, exonic, or intronic and exonic regions of the reference. By default it seeks matches in intronic regions (intronExon='intron').
`sujectGeneNamesCol`	The column in the row data of the subject that includes the gene names.
`repeatsTableToFilter`	A data.frame table that includes chr,begin and end columns. If defined, all reads mapped to the described regions will be ingnored.
`scaleFragment`	Logical value, indicating whether the retention levels must be scaled by (genewide) fragment levels.
`scaleLength`	Logical value, indicating whether the retention levels must be scaled by length of the introns/exons.
`unmapValue`	The value to assign to unmapped rows (i.e. introns/exons).
`FUN`	The function to apply.
`...`	Other parameter settings from `aggregate()` function.

The returned value is a data frame if replaceValues is FALSE and it is SummarizedExperiment if replaceValues is TRUE.

Ali Oghabian

readInterestResults interest interest.sequential

mdsChr22Obj

tmp<- applyOverlap(
	query=mdsChr22Obj,
	subject=mdsChr22Obj,
	type="equal",
	replaceValues=FALSE,
	intExCol="int_ex", 
	intronExon="intron",
	sujectGeneNamesCol="collapsed_transcripts",
	scaleFragment=TRUE,
	scaleLength=TRUE,
	unmapValue=0,
	FUN=head,
	n=1
)