fitted.snm: Extract fitted values from an snm object

In Sage-Bionetworks/snm: Supervised Normalization of Microarrays

Description

Computes fitted values under models used in snm normalization.

Usage

snm.fitted(object, ...)
## S3 method for class 'snm'
fitted(object, ...)

Arguments

object	Output from the snm function.
...	Not used.

Details

Returns the fitted values under the "null model" (adjustment variables only) and the "full model" (adjustment variables + biological variables).

Value

fit0	Linear model fits when regression each probe's normalized data on the null model, ~adj.var.
fit1	Linear model fits when regression each probe's normalized data on the full model, ~adj.var+bio.var.

Note

These fits are useful for investigating the quality of the study-specific model used in the normalization. For example, the residuals can be obtained from the full model fit and examined for latent structure.

Author(s)

John D. Storey <[e-mail]>

References

Mecham BH, Nelson PS, Storey JD (2010) Supervised normalization of microarrays. Bioinformatics, 26: 1308-1315.

See Also

snm, sim.singleChannel

Examples

## Not run: 
singleChannel <- sim.singleChannel(12345)
snm.obj <- snm(singleChannel$raw.data,
		      singleChannel$bio.var,
		      singleChannel$adj.var[,-6],
		      singleChannel$int.var, num.iter=10)
snm.fit = fitted(snm.obj)
res1 = snm.obj$norm.dat - snm.fit$fit1
snm.svd = fast.svd(res1)
cor(snm.svd$v[,1], singleChannel$adj.var[,6])
plot(snm.svd$v[,1], singleChannel$adj.var[,6])

## End(Not run)

Sage-Bionetworks/snm documentation built on May 9, 2019, 12:14 p.m.