biomvRCNS (version 1.12.0)

biomvRmgmr: Batch process multiple sequences and samples using max-gap-min-run algorithm for 2 states segmentation

Description

This is a wrapper function for batch processing multiple sequences and samples using max-gap-min-run algorithm for 2 states segmentation

Usage

biomvRmgmr(x, xPos=NULL, xRange=NULL, usePos='start', cutoff=NULL, q=0.9, high=TRUE, minrun=5, maxgap=2, splitLen=Inf, poolGrp=FALSE, grp=NULL, cluster.m=NULL, avg.m='median', trim=0,na.rm=TRUE)

Arguments

x

input data matrix, or a GRanges object with input stored in the meta DataFrame, assume ordered.

xPos

a vector of positions for each x row

xRange

a IRanges/GRanges obejct, same length as x rows

usePos

character value to indicate whether the 'start', 'end' or 'mid' point position should be used

cutoff

threshold level above which is considered extreme

q

relative quantile threshold level instead of absolute value for the cutoff

high

TRUE if the cutoff or q here is the lower bound and values greater than the threshold are considered

minrun

minimum run length for the resulting segments

maxgap

maximum genomic distance below which two adjacent qualified tiles can be joined

splitLen

numeric value, maximum length of segments, split if too long

poolGrp

TRUE if samples within the same group should be pooled using median for each feature

grp

vector of group assignment for each sample, with a length the same as columns in the data matrix, samples within each group would be processed simultaneously if a multivariate emission distribution is available

cluster.m

clustering method for prior grouping, possible values are 'ward','single','complete','average','mcquitty','median','centroid'

avg.m

method to calculate average value for each segment, 'median' or 'mean' possibly trimmed

trim

the fraction (0 to 0.5) of observations to be trimmed from each end of x before the mean is computed. Values of trim outside that range are taken as the nearest endpoint.

na.rm

TRUE if NA value should be ignored

Value

A biomvRCNS-class object:

x:

Object of class "GRanges", with range information either from real positional data or just indices, with input data matrix stored in the meta columns.

res:

Object of class "GRanges" , each range represent one continuous segment identified, with sample name slot 'SAMPLE' and segment mean slot 'MEAN' stored in the meta columns

param:

Object of class "list", list of all parameters used in the model run.

Details

This is the batch function to apply maxGapminRun multiple sequence.

See Also

biomvRhsmm maxGapminRun

Examples

	data(coriell)
	xgr<-GRanges(seqnames=paste('chr', coriell[,2], sep=''), IRanges(start=coriell[,3], width=1, names=coriell[,1]))
	values(xgr)<-DataFrame(coriell[,4:5], row.names=NULL)
	xgr<-xgr[order(xgr)]
	resseg<-biomvRmgmr(x=xgr, minrun=3000, maxgap=1500, q=0.9, grp=c(1,2))