biomvRmgmr: Batch process multiple sequences and samples using...
In biomvRCNS: Copy Number study and Segmentation for multivariate biological data

Description Usage Arguments Details Value Author(s) See Also Examples

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

1	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)

`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

This is the batch function to apply maxGapminRun multiple sequence.

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.

Yang Du

biomvRhsmm maxGapminRun

	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))