CSAR (version 1.24.0)

sigWin: Calculate regions of read-enrichment

Description

Calculate regions of read-enrichment

Usage

sigWin(experiment, t = 1, g = 100)

Arguments

experiment

Output of the function ChIPseqScore

t

Numeric value. Read-enriched regions are calculated as genomic regions with score values bigger than t

g

Integer value. The maximum gap allowed between regions. Regions that are less than g bps away will be merged.

Value

An object of type'GRange' with its values being:

seqnames

Chromosome name

ranges

An IRanges object indicating start and end of the read-enriched region

posPeak

Position of the maximum score value on the read-enriched region

score

Maximum score value on the read-enriched region

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

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 a score for each nucleotide position
test<-ChIPseqScore(control=nhitsC,sample=nhitsS)

##We calculate the candidate read-enriched regions
win<-sigWin(test)