QCinfo | R Documentation |
Extract informations for data quanlity controls: detection P values, number of beads and averaged bisulfite conversion intensity. The function can also identify low quality samples and probes, as well as outlier samples based on total intensity or beta value distribution.
QCinfo(rgSet, detPthre=0.000001, nbthre=3, samplethre=0.05, CpGthre=0.05,
bisulthre=NULL, outlier=TRUE, distplot=TRUE)
rgSet |
An object of class |
detPthre |
Detection P value threshold to identify low quality data point |
nbthre |
Number of bead threshold to identify low quality data point |
samplethre |
Threshold to identify low quality samples, the percentage of low quality methylation data points across probes for each sample |
CpGthre |
Threshold to identify low quality probes, percentage of low quality methylation data points across samples for each probe |
bisulthre |
Threshold of bisulfite intensity for identification of low quality samples. By default, Mean - 3 x SD of sample bisufite control intensities will be used as the threshold. |
outlier |
If TRUE, outlier samples in total intensity or beta value distribution will be idenfied and classified as bad samples. |
distplot |
TRUE or FALSE, whether to produce beta value distribution plots before and after QC. |
detP: a matrix of detection P values
nbead: a matrix for number of beads
bisul: a vector of averaged intensities for bisulfite conversion controls
badsample: a list of low quality or outlier samples
badCpG: a list of low quality CpGs
outlier_sample: a list of outlier samples
Figure "qc_sample.jpg": scatter plot for Percent of low quality data per sample and Average bisulfite conversion intensity
Figure "qc_CpG.jpg": histogram for Percent of low quality data per CpG.
Figure "freqpolygon_beta_beforeQC.jpg": distribution plot before filtering.
Figure "freqpolygon_beta_afterQC.jpg": distribution plot after filtering.
Zongli Xu
Zongli Xu, Liang Niu, Leping Li and Jack A. Taylor, ENmix: a novel background correction method for Illumina HumanMethylation450 BeadChip. Nucleic Acids Research 2015.
if(FALSE){
if (require(minfiData)) {
sheet <- read.metharray.sheet(file.path(find.package("minfiData"),"extdata"), pattern = "csv$")
rgSet <- read.metharray.exp(targets = sheet,extended = TRUE)
qcscore<-QCinfo(rgSet)
}}
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