CSAR (version 1.24.0)

ChIPseqScore: Calculate read-enrichment scores for each nucleotide position

Description

Calculate read-enrichment scores for each nucleotide position

Usage

ChIPseqScore(control, sample, backg = -1, file = NA, norm = 3 * 10^9,  test = "Ratio",times=1e6,digits=2)

Arguments

control

data.frame structure obtained by mappedReads2Nhits

sample

data.frame structure obtained by mappedReads2Nhits

backg

Due low coverage in the control, there could be regions with no hits. Any region with a hit value lower than backg in the control will be set to the value of backg

file

Name of the file where you wan to save the results (if desired)

norm

Integer value. Number of hits will be reported by number of hits per norm nucleotides

test

Use a score based on the poisson distribution ("Poisson") or in the ratio ("Ratio")

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

digits

Number of decimal digits used to report the score values

Value

A list to be used for other functions of the CSAR package

chr

Chromosme names

chrL

Chromosme length (bp)

filenames

Name of the files where the score values are storaged

digits

Score values storaged on the files need to be divided by 10^digits

Details

Different sequencing efforts yield different number of sequenced reads, for this reason the "number of hits" at each nucleotide position is normalized by the total number of nucleotides sequenced. Subsequently, the number of hits for the sample is normalize to have the same mean and variance than the control, for each chromosome independently or for the whole set of chromosomes (depending of the value of normEachChrInd). Due low coverage, there could be regions with no hits. Any region with a hit value lower than backg in the control will be set to the value of backg For each nucleotide position, a read-enrichment score will be calculated with the Poisson test, or with the ratio.

References

Muino et al. (submitted). Plant ChIP-seq Analyzer: An R package for the statistical 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)