estParam: estimate simulation parameters from a count table
In PROPER: PROspective Power Evaluation for RNAseq

Description Usage Arguments Details Value Author(s) Examples

This function estimate simulation parameters from a count table, which can be used to set simulation scenarios. The parameters estimated include baseline expression, biological variation in the form of dispersion paramter.

1	estParam(X,type = c(1,2))

`X`	An ExpressionSet or a matrix, with entries being RNA sequencing counts
`type`	`type=1` estimates with minimal assumption based on sample means and variances for each genes. `type=2` uses `edgeR` package.

This is a function that allows a user to establish simulation basis from his/her own data set. Type 1 uses simple average count and sample variance to estimate over dispersion, after normalizing by library size for each sample. Estimated dispersion is bounded at minimum 0.001. Type 2 uses edgeR's AveLogCPM as the estiamte for baseline expression and tagwiseDispersion as the estimate for dispersion.

A list with following fields:

`seqDepth`	Estimated sequencing depth for each sample
`lmean`	A vector of baseline expression rate per gene in log scale, with length `nrow(X)`
`lOD`	A vector of log dispersion for each gene, with length `nrow(X)`

Jean Wu <zhijin_wu@brown.edu>

## Not run: 
lmu0=rnorm(20000,5,2)
lOD0=rnorm(20000,-4,1)
lmu=exp(rnorm(20000*10,lmu0,exp(lOD0)))
X=matrix(rpois(20000*10,lmu),20000,10)
param=estParam(X)

## End(Not run)