classify.events: Classify splicing events
In jmonlong/sQTLseekeR: Splicing QTL discovery tool

Description Usage Arguments Details Value Author(s) Examples

Find the splicing event(s) that differenciate pairs of transcripts.

1	classify.events(df, trans.struct)

`df`	a data.frame that includes pairs of transcript IDs in columns 'tr.first' and 'tr.second'.
`trans.struct`	a data.frame with the transcript structure, i.e. the location of its exons and eventually its UTRs. See Details for format.

The input transcript structure is a data.frame with information about the CDSs and UTRs start/end positions as well as the DNA strand. The columns should be: 'transId' for the transcript ID; 'strand' for the DNA strand; 'cdsStart' for the CDS start positions; 'cdsEnds' for the end positions; 'utrStarts' and 'utrEnds' for the UTRs. The position in 'cdsStarts'/'cdsEnds'/'utrStart'/'utrEnds' must be a concatenation of the position with ',' as separator. See example.

The classification code follows mostly the one defined by AStalavista (http://genome.crg.es/astalavista/FAQ.html). Numbers represent exon boundaries and are ordered by genomic position, '-' represents exon body, '^' a splice junction and ')' the end of the transcript. The state of the two transcript is separated by a ','. For example, '1-2^,3-4^' represent mutually exclusive exons, ',1^2-' means intron retention. In addition, we added an extra formatting: '<>' means that the event involves UTRs. Hence '<>,1^),2^)' means alternative 3' UTR.

a list with

`res`	input data.frame with two new columns: 'classCode' and 'classEvent'. See Details for interpretation.
`stats`	a data.frame with the occurence of each event in the data.

Jean Monlong

## Creating a fake transcript structure
tr.str = data.frame(transId=c("t1","t2","t3"),strand="+",
cdsStarts=c("10,40,100","10,20,100","10,40,100"),
cdsEnds=c("15,55,130","15,30,130","15,55,130"),
utrStarts=c("5,130","5,130","5,130"),
utrEnds=c("10,135","10,135","10,150"))
tr.str

## Creating the data.frame with the transcript pairs
tr.df = data.frame(tr.first=c("t1","t1"), tr.second=c("t2","t3"))

## Calling the function
classify.events(tr.df, tr.str)