sigWin {CSAR} | R Documentation |
Calculate regions of read-enrichment
sigWin(experiment, t = 1, g = 100)
experiment |
Output of the function |
t |
Numeric value. Read-enriched regions are calculated as genomic regions with score values bigger than |
g |
Integer value. The maximum gap allowed between regions. Regions that are less than |
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 |
Jose M Muino, jose.muino@wur.nl
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.
CSAR-package
##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)