snm.fitted {snm} | R Documentation |
Computes fitted values under models used in snm
normalization.
snm.fitted(object, ...) ## S3 method for class 'snm' fitted(object, ...)
object |
Output from the |
... |
Not used. |
Returns the fitted values under the "null model" (adjustment variables only) and the "full model" (adjustment variables + biological variables).
fit0 |
Linear model fits when regressing each probe's normalized data on the null model, |
fit1 |
Linear model fits when regressing each probe's normalized data on the full model, |
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.
John D. Storey <jstorey@princeton.edu>
Mecham BH, Nelson PS, Storey JD (2010) Supervised normalization of microarrays. Bioinformatics, 26: 1308-1315.
## 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)