readCounts: A list object that should be used as input to optimization...
In rxSeq: Combined Total and Allele Specific Reads Sequencing Study

Description Value Author(s) See Also Examples

It should contain at least total read counts (TReC) and classification of crosses 1 to 8. To fit the full model should also have appropriate allele specific counts n and n0B. Also is used along with results of optimization as input to nLogLik function if one needs to calculate Hessian matrix.

`index`	vector defining the cross of the mouse, female - AB=1, BA=2, AA=3, BB=4, and male - AB=5, BA=6, AA=7, BB=8. If mice are of only one sex, AB=1, BA=2, AA=3, BB=4.
`y`	matrix of TReC counts. Note, the expected input assumes that inbred mice will be in the last columns of the table, after the last F1 mouse.
`n`	matrix of ASE counts for corresponding F1 mouse (classes 1,2,5,6) for corresponding genes.
`n0B`	matrix of ASE counts belonging for allele B, for correponding genes and mice as in n.
`kappas`	A parameter, specifying as overall TReC for the mouse, on log scale
`tausB`	Xce effect: expression of allele B relative to the overall allele specific count for each mouse. Set to NULL in autosomes.
`gene.switch`	For which genes Xce effect should be switched. Null for autosomes.
`geneids`	ids of genes, if not provided, rownames of the matrix y will be used
`chrom`	this field would be set to be "X" since this is dataset for chromosome X
`model`	set to be "full", can be modified to "short" to run a TReC oply model
`geneids`	Ensembl gene ids
`tech.ctrl`	a list of overdispersion boundaries and log(2)

Vasyl Zhabotynsky vasyl@unc.edu

process,nLogLik, simRX.

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# see total read counts (TReC) for first 2 X chromosome genes of a data example:
rcA = readCounts(index=data.A$index, y=data.A$y[1:2,], n=data.A$n[1:2,], n0B=data.A$n0B[1:2,], 
                 kappas=data.A$kappas, geneids=data.A$geneids[1:2])