plotMotif: Correlation Motif Plot

In iASeq: iASeq: integrating multiple sequencing datasets for detecting allele-specific events

Description

This function plots the Correlation Motif patterns, the associated prior probability distributions and the number of SNPs called for each motif based on posterior probability.

Usage

plotMotif(bestmotif,title="",cutoff)

Arguments

bestmotif	The bestmotif obtained from iASeqmotif.
title	The title on the figure.
cutoff	The posterior probability cutoff for calling a SNP belonging to certain motif.

Details

Each row in all graphs corresponds to one motif pattern. The first graph shows qup, the correlation motif pattern of over expression (binding). The second graph shows qdown, the correlation motif pattern of under expression (binding). The grey color scale of cell (k,d) indicates the probability that motif k is over or under expressed in study d. Each row of the two bar charts corresponds to the motif pattern in the same row of the left two pattern graphs. The length of the bar in the first bar chart estimates the number of SNPs of the given pattern in the dataset according to motif frequency, which is equal to motif.fitted\$bestmotif\$motif.prior multiplying the number of total SNPs. The length of the bar in the second bar chart shows the number of SNPs called for the given pattern according to the cutoff of posterior probability.

Author(s)

Yingying Wei, Hongkai Ji

References

Yingying Wei, Xia Li, Qianfei Wang, Hongkai Ji (2012) iASeq: integrating multiple ChIP-seq datasets for detecting allele-specific binding.

See Also

iASeqmotif, plotBIC, sampleASE

Examples

example(iASeqmotif) # compute 'motif.fitted'
plotMotif(motif.fitted$bestmotif,cutoff=0.9)

iASeq documentation built on Nov. 8, 2020, 5:36 p.m.