importC {HiTC} | R Documentation

## Import high-htroughput 'C' data

### Description

Import 5C or Hi-C data from list file

### Usage

    importC(con, xgi.bed, ygi.bed=NULL, allPairwise=FALSE,
    rm.trans=FALSE, lazyload=FALSE)

### Arguments

`con` | input csv file. See details
`xgi.bed` | BED file describing the 'x' Intervals (i.e. column names) of the contact map
`ygi.bed` | BED file describing the 'y' intervals (i.e. row names) of the contact map
`allPairwise` | logical; generate all pairwise chromosomal contact maps, i.e chr1-chr2, chr2-chr1
`rm.trans` | if true, returns only intra-chromosomal maps
`lazyload` | logical; see details

### Details

This function import high-throughput data from a tab list file.
The standard format for 5C/Hi-C data is the following :
** One list file (tab delimited) bin1 bin2 x12 bin1 bin3 x13 ... ** The BED file(s) describing the intervals ('xgi.bed' and 'ygi.bed' are usually the same for Hi-C but can be different for 5C data) chr1 1 1000000 bin1 chr1 1000001 2000000 bin2 ...

Note that this format is particularly interesting for sparse data as only non null values are stored.

The lazyload option allow to reduce the memory size of imported object. Therefore, only half of inter-chromosomal maps are stored. And intra-chromosomal maps are stored as sparse triangular matrix. Note that even if the contact maps are stored as triangular matrix, the indata method always returns a symmetrical map.

### Value

A `HTClist` object

### Author(s)

N. Servant

### See Also

`exportC`,`import.my5C`, `HTCexp-class`

### Examples

    ## Not run:
    data(Nora_5C)

    ## Data binning
    E14.bin<-binningC(E14$chrXchrX)

    ## Export the new intervals definition
    exportC(E14.bin, file="E14")

    ##Import
    importC(con="E14.count", xgi="E14_xgi.bed", ygi="E14_ygi.bed")

    ## End(Not run)

[Package HiTC version 1.30.0 Index]