Description Usage Arguments Details Value Note Author(s) References See Also Examples
This function implements the method of McLachLan, Bean and Jones (2006).
1 |
p |
a numeric vector the p-values |
theoretical.null |
logical scalar, indicating whether theoretical N(0,1) null distribution is assumed for z-scores. |
start.pi0 |
optional numeric scalar, starting value of pi0 for EM algorithm; if missing, |
eps |
numeric scalar, maximum tolerable absolute difference of parameter estimates for successive iterations in the EM algorithm. |
niter |
numeric scalar, maximum number of EM iterations. |
verbose |
logical scalar, indicating whether excessive outputs will be printed during EM algorithm. |
A two-component normal mixture model is fit thru EM algorithm on the z-scores, where z=qnorm(1-p)
.
A length 5 numeric named vector of estimated parameters, with class 'znormix' and attributes
theoretical.null |
the same as input. |
converged |
logical, convergence status. |
iter |
numeric, number of iterations. |
call |
the |
lfdr |
numeric vector of local false discovery rates, with order being the same as the input p-values. |
fdr |
numeric vector of false discovery rates, with order being the same as the input p-values. |
There are two small differences with McLachlan, Bean and Jones (2006):
If start.pi0
is missing, it is estimated by the q-value smoother method implimented in qvalue
.
For the empirical null case, a call to quantile(z, start.pi0)
is used as the threshold to determine the initial component assignment, when choosing starting values.
Long Qu
G.J. McLachlan, R.W. Bean and L. Ben-Tovim Jones. (2006) A Simple implementation of a normal mixture approach to differential gene expression in multiclass microarrays. Bioinformatics, 22(13):1608-1615.
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