get_usage4plot {InPAS} | R Documentation

## prepare coverage data and fitting data for plot

### Description

prepare coverage data and fitting data for plot

### Usage

    get_usage4plot(gr, proximalSites, sqlite_db, hugeData)

### Arguments

`gr` | an object of GenomicRanges::GRanges
`proximalSites` | An integer(n) vector, specifying the coordinates of proximal CP sites. Each of the proximal sites must match one entry in the GRanges object, `gr`.
`sqlite_db` | A path to the SQLite database for InPAS, i.e. the output of `setup_sqlitedb()`.
`hugeData` | A logical(1), indicating whether it is huge data

### Value

An object of GenomicRanges::GRanges with metadata:

`dat` | A data.frame, first column is the position, the other columns are Coverage and value
`offset` | offset from the start of 3' UTR

### Author(s)

Jianhong Ou, Haibo Liu

### Examples

       library(BSgenome.Mmusculus.UCSC.mm10)
       library(TxDb.Mmusculus.UCSC.mm10.knownGene)
       genome <- BSgenome.Mmusculus.UCSC.mm10
       TxDb <- TxDb.Mmusculus.UCSC.mm10.knownGene

       ## load UTR3 annotation and convert it into a GRangesList
       data(utr3.mm10)
       utr3 <- split(utr3.mm10, seqnames(utr3.mm10))

       bedgraphs <- system.file("extdata",c("Baf3.extract.bedgraph",
                                            "UM15.extract.bedgraph"),
                               package = "InPAS")
       tags <- c("Baf3", "UM15")
       metadata <- data.frame(tag = tags,
                              condition = c("baf", "UM15"),
                              bedgraph_file = bedgraphs)
       outdir = tempdir()
       write.table(metadata, file =file.path(outdir, "metadata.txt"),
                   sep = "\t", quote = FALSE, row.names = FALSE)

       sqlite_db <- setup_sqlitedb(metadata = file.path(outdir,
                                                        "metadata.txt"),
                                   outdir)
       coverage <- list()
       for (i in seq_along(bedgraphs)){
       coverage[[tags[i]]] <- get_ssRleCov(bedgraph = bedgraphs[i],
                                tag = tags[i],
                                genome = genome,
                                sqlite_db = sqlite_db,
                                outdir = outdir,
                                removeScaffolds = TRUE,
                                BPPARAM = NULL)
       }
       coverage_files <- assemble_allCov(sqlite_db,
                                         outdir,
                                         genome,
                                         removeScaffolds = TRUE)

       data4CPsSearch <- setup_CPsSearch(sqlite_db,
                                         genome,
                                         utr3,
                                         background = "10K",
                                         TxDb = TxDb,
                                         removeScaffolds = TRUE,
                                         BPPARAM = NULL,
                                         hugeData = TRUE,
                                         outdir = outdir)

       gr <- GRanges("chr6", IRanges(128846245, 128850081), strand = "-")
       names(gr) <- "chr6:128846245-128850081"
       data4plot <- get_usage4plot(gr,
                                   proximalSites = 128849148,
                                   sqlite_db,
                                   hugeData = TRUE)
       plot_utr3Usage(usage_data = data4plot,
                      vline_color = "purple",
                      vline_type = "dashed")

[Package InPAS version 2.2.0 Index]