CPsites {InPAS} | R Documentation

## predict the cleavage and polyadenylation(CP) site

### Description

predict the alternative cleavage and polyadenylation (CP or APA) site.

### Usage

        CPsites(coverage, groupList=NULL, genome, utr3,
            window_size=100, search_point_START=50, search_point_END=NA,
            cutStart=window_size, cutEnd=0, adjust_distal_polyA_end=TRUE,
            coverage_threshold=5, long_coverage_threshold=2,
            background=c("same_as_long_coverage_threshold",
                         "1K", "5K", "10K", "50K"),
            txdb=NA,
            PolyA_PWM=NA, classifier=NA, classifier_cutoff=.8, step=1,
            two_way=FALSE,
            shift_range=window_size,
            BPPARAM=NULL, tmpfolder=NULL, silence=TRUE)

### Arguments

`coverage` | coverage for each sample, output of coverageFromBedGraph
`groupList` | group list of tag names
`genome` | an object of BSgenome
`utr3` | output of utr3Annotation
`window_size` | window size for noval distal position searching and adjusted polyA searching, default: 100
`search_point_START` | start point for searching
`search_point_END` | end point for searching
`cutStart` | how many nucleotides should be removed from the start before search, 0.1 means 10 percent, 25 means cut first 25.
`cutEnd` | how many nucleotides should be removed from the end before search, 0.1 means 10 percent.
`adjust_distal_polyA_end` | If true, adjust distal polyA end by cleanUpdTSeq
`coverage_threshold` | cutoff coverage threshold for first 100 nucleotides. If the coverage of first 100 nucleotides is lower than coverage_threshold, that transcript will be dropped.
`long_coverage_threshold` | cutoff threshold for coverage in the region of long form. If the coverage in the region of long form is less than long_coverage_threshold, that transcript will be dropped.
`background` | the range for calculating cutoff threshold of local background
`txdb` | an object of TxDb
`PolyA_PWM` | Position Weight Matrix of polyA
`classifier` | An object of class `"PASclassifier"`
`classifier_cutoff` | This is the cutoff used to assign whether a putative pA is true or false. This can be any floating point number between 0 and 1. For example, classifier_cutoff = 0.5 will assign an putative pA site with prob.1 > 0.5 to the True class (1), and any putative pA site with prob.1 <= 0.5 as False (0).
`step` | adjust step, default 1, means adjust by each base by cleanUpdTSeq.
`two_way` | Search the proximal site from both direction or not.
`shift_range` | the shift range for polyA site searching
`BPPARAM` | An optional `BiocParallelParam` instance determining the parallel back-end to be used during evaluation, or a list of BiocParallelParam instances, to be applied in sequence for nested calls to bplapply.
`tmpfolder` | temp folder could save and reload the analysis data for resume analysis.
`silence` | report progress or not. default not report.

### Value

return an object of GRanges contain the estimated CP sites.

### Author(s)

Jianhong Ou

### References

ref: Cheung MS, Down TA, Latorre I, Ahringer J. Systematic bias in high-throughput sequencing data and its correction by BEADS. Nucleic Acids Res. 2011 Aug;39(15):e103. doi: 10.1093/nar/gkr425. Epub 2011 Jun 6. PubMed PMID: 21646344; PubMed Central PMCID: PMC3159482.

mappability could be calculated by [GEM](http://algorithms.cnag.cat/wiki/Man:gem-mappability)

ref: Derrien T, Estelle J, Marco Sola S, Knowles DG, Raineri E, Guigo R, Ribeca P. Fast computation and applications of genome mappability. PLoS One. 2012;7(1):e30377. doi: 10.1371/journal.pone.0030377. Epub 2012 Jan 19. PubMed PMID: 22276185; PubMed Central PMCID: PMC3261895.

### Examples

        if(interactive()){
            library(BSgenome.Mmusculus.UCSC.mm10)
            path <- file.path(find.package("InPAS"), "extdata")
            bedgraphs <- file.path(path, "Baf3.extract.bedgraph")
            data(utr3.mm10)
            tags <- "Baf3"
            genome <- BSgenome.Mmusculus.UCSC.mm10
            coverage <-
                coverageFromBedGraph(bedgraphs, tags, genome, hugeData=FALSE)
            CP <- CPsites(coverage=coverage, gp1=tags, gp2=NULL, genome=genome,
                utr3=utr3.mm10, coverage_threshold=5, long_coverage_threshold=5)
        }

[Package InPAS version 1.20.0 Index]