Obtain the read-enrichment score distribution under the null hypothesis

Description

Obtain the read-enrichment score distribution under the null hypothesis

Usage

getPermutatedWinScores(file, nn)

Arguments

Value

Numeric vector of score values under permutation

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.

See Also

CSAR-package, permutatedWinScores

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 posotion 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))


##We calculate two sets of read-enrichment scores through permutation
permutatedWinScores(nn=1,sample=sampleSEP3_test,control=controlSEP3_test,fileOutput="test",chr=c("CHR1v01212004"),chrL=c(100000))
permutatedWinScores(nn=2,sample=sampleSEP3_test,control=controlSEP3_test,fileOutput="test",chr=c("CHR1v01212004"),chrL=c(100000))

###Next function will get all permutated score values generated by permutatedWinScores function. 
##This represent the score distribution under the null hypotesis and therefore it can be use to control the error of our test.
nulldist<-getPermutatedWinScores(file="test",nn=1:2)

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
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> 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/getPermutatedWinScores.Rd_%03d_medium.png", width=480, height=480)
> ### Name: getPermutatedWinScores
> ### Title: Obtain the read-enrichment score distribution under the null
> ###   hypothesis
> ### Aliases: getPermutatedWinScores
> 
> ### ** 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 posotion 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 ...
> 
> 
> ##We calculate two sets of read-enrichment scores through permutation
> permutatedWinScores(nn=1,sample=sampleSEP3_test,control=controlSEP3_test,fileOutput="test",chr=c("CHR1v01212004"),chrL=c(100000))
mappedReads2Nhits has just finished   CHR1v01212004 ...
mappedReads2Nhits has just finished   CHR1v01212004 ...
CHR1v01212004  done...
CHR1v01212004 done...
Win file for permutation 1 can be found at test-1.permutatedWin
> permutatedWinScores(nn=2,sample=sampleSEP3_test,control=controlSEP3_test,fileOutput="test",chr=c("CHR1v01212004"),chrL=c(100000))
mappedReads2Nhits has just finished   CHR1v01212004 ...
mappedReads2Nhits has just finished   CHR1v01212004 ...
CHR1v01212004  done...
CHR1v01212004 done...
Win file for permutation 2 can be found at test-2.permutatedWin
> 
> ###Next function will get all permutated score values generated by permutatedWinScores function. 
> ##This represent the score distribution under the null hypotesis and therefore it can be use to control the error of our test.
> nulldist<-getPermutatedWinScores(file="test",nn=1:2)
Read 73 items
Read 66 items
> 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>