calculatePosteriorAvg: Calculate the posterior average for indicators of concordant...

In XDE: XDE: a Bayesian hierarchical model for cross-study analysis of differential gene expression

Description

This function calculates the posterior average for indicators of concordant and discordant differential expression from the saved log files. See details.

Usage

calculatePosteriorAvg(object, NCONC=2, NDIFF=1, burnin=0)

Arguments

object	Object of class XdeMcmc
NCONC	Integer: number of studies for which the gene must be differentially expressed (in the same direction) to be classified as concordant differential expression
NDIFF	Integer: number of studies for which a gene must be up- or down-regulated to be classified as differentially expressed. It is the union of concordant and discordant differential expression.
burnin	Integer: number of MCMC iterations for the burnin. Posterior means are computed from the MCMC samples following burnin.

Details

For each iteration,

1. calculate the sign of delta * Delta

2. For each gene, compute the number of positive signs (P) and the number of negative signs (N) (a G x 2 matrix, where G is the number of genes in common across all studies). P + N is <= S, where S is the number of studies.

3. for a given gene, the discordant indicator is simply when P * N is nonzero.

4. The concordant indicator requires P * N = 0 AND P + N >= NCONC, where NCONC is specified by the user.

5. differential expression is simply | P | + | N | >= NDIFF. By default, NDIFF is 1 but can be user-specified.

The posterior average is then computed from the mean over all MCMC iterations.

Value

A G x 3 matrix.

Author(s)

RS

See Also

posteriorAvg

XDE documentation built on Nov. 8, 2020, 5:02 p.m.