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Last data update: 2014.03.03

R: Save the read-enrichment scores at each nucleotide position...

score2wig

R Documentation

Save the read-enrichment scores at each nucleotide position in a .wig file format

Description

Save the read-enrichment scores at each nucleotide position in a .wig file format that can be visualize by a genome browser (eg: Integrated Genome Browser)

Usage

score2wig(experiment, file, t = 2, times = 1e6,description="", name="")

Arguments

`experiment`	Output of the function `ChIPseqScore`
`file`	Name of the output .wig file
`t`	Only nucleotide positions with a read-enrichment score bigger than `t` will be reported
`times`	To be memory efficient, CSAR will only upload to the RAM memory fragments of length `times`. A bigger value means more RAM memory needed but whole process will be faster
`description`	Character. It adds a description to the wig file. The description will be shown by the genome browser used to visualize the wig file.
`name`	Character. It adds a wig to the wig file. The name will be shown by the genome browser used to visualize the wig file.

Value

None. Results are printed in a file

Author(s)

Jose M Muino, jose.muino@wur.nl

References

Muino et al. (submitted). Plant ChIP-seq Analyzer: An R package for the statistcal detection of protein-bound genomic regions.
Kaufmann et al.(2009).Target genes of the MADS transcription factor SEPALLATA3: integration of developmental and hormonal pathways in the Arabidopsis flower. PLoS Biology; 7(4):e1000090.

Examples


##For this example we will use the a subset of the SEP3 ChIP-seq data (Kaufmann, 2009)
data("CSAR-dataset");
##We calculate the number of hits for each nucleotide position for the control and sample. We do that just for chromosome chr1, and for positions 1 to 10kb
nhitsS<-mappedReads2Nhits(sampleSEP3_test,file="sampleSEP3_test",chr=c("CHR1v01212004"),chrL=c(10000))
nhitsC<-mappedReads2Nhits(controlSEP3_test,file="controlSEP3_test",chr=c("CHR1v01212004"),chrL=c(10000))

##Since we will not need the raw data anymore, we could delete it from the RAM memory
rm(sampleSEP3_test,controlSEP3_test);gc(verbose=FALSE)
##We calculate a score for each nucleotide position
test<-ChIPseqScore(control=nhitsC,sample=nhitsS)

##We generate a wig file of the results to visualize them in a genome browser
score2wig(test,file="test.wig")

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

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'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(CSAR)
Loading required package: S4Vectors
Loading required package: stats4
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:stats':

    IQR, mad, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, cbind, colnames, do.call, duplicated, eval, evalq,
    get, grep, grepl, intersect, is.unsorted, lapply, lengths, mapply,
    match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, rank,
    rbind, rownames, sapply, setdiff, sort, table, tapply, union,
    unique, unsplit


Attaching package: 'S4Vectors'

The following objects are masked from 'package:base':

    colMeans, colSums, expand.grid, rowMeans, rowSums

Loading required package: IRanges
Loading required package: GenomeInfoDb
Loading required package: GenomicRanges
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/CSAR/score2wig.Rd_%03d_medium.png", width=480, height=480)
> ### Name: score2wig
> ### Title: Save the read-enrichment scores at each nucleotide position in a
> ###   .wig file format
> ### Aliases: score2wig LoadBinCSAR
> 
> ### ** Examples
> 
> 
> ##For this example we will use the a subset of the SEP3 ChIP-seq data (Kaufmann, 2009)
> data("CSAR-dataset");
> ##We calculate the number of hits for each nucleotide position for the control and sample. We do that just for chromosome chr1, and for positions 1 to 10kb
> nhitsS<-mappedReads2Nhits(sampleSEP3_test,file="sampleSEP3_test",chr=c("CHR1v01212004"),chrL=c(10000))
mappedReads2Nhits has just finished   CHR1v01212004 ...
> nhitsC<-mappedReads2Nhits(controlSEP3_test,file="controlSEP3_test",chr=c("CHR1v01212004"),chrL=c(10000))
mappedReads2Nhits has just finished   CHR1v01212004 ...
> 
> ##Since we will not need the raw data anymore, we could delete it from the RAM memory
> rm(sampleSEP3_test,controlSEP3_test);gc(verbose=FALSE)
          used (Mb) gc trigger  (Mb) max used (Mb)
Ncells 1311311 70.1    2164898 115.7  1589692 84.9
Vcells 1078968  8.3    2060183  15.8  1650136 12.6
> ##We calculate a score for each nucleotide position
> test<-ChIPseqScore(control=nhitsC,sample=nhitsS)
Error in while (j <= chrL) { : argument is of length zero
Calls: ChIPseqScore
Execution halted