UL.mod.cv: A glmnet-object trained to perform gestational age...

In JonBohlin/predictGA: Prediction of gestational age with Illumina HumanMethylation450 data

Description

The glmnet-object consists of a Lasso-regression model 'trained' to perform gestational age predictions. It is called by the wrapper function predictGA, which is more user-friendly.

Details

The trained Lasso-model contains cross-validated estimates of the penalty term lambda that regulates the number of CpG sites needed for gestational age prediction. It is called by the glmnet-inherited predict function with a matrix of CpG betas (with values between 0 and 1) that conforms to the Illumina HumanMethylation450 platform. The gestational age estimates used to train the regression model were taken from the MoBa cohort and are based on ultrasound.

Source

Magnus P, Irgens LM, Haug K, Nystad W, Skjaerven R, Stoltenberg C, MoBa Study Group. Cohort profile: the Norwegian mother and child cohort study (MoBa). International journal of epidemiology. 2006 Oct 1;35(5):1146-50.

References

Jerome Friedman, Trevor Hastie, Robert Tibshirani (2010). Regularization Paths for Generalized Linear Models via Coordinate Descent. Journal of Statistical Software, 33(1), 1-22. URL http://www.jstatsoft.org/v33/i01/.

Examples

## Extract all non-zero regression coefficients
temp<-as.matrix(coef(UL.mod.cv))
allNonZeroCoefs<-rownames(temp)[temp[,1]!=0]
allNonZeroCoefs[-1]

JonBohlin/predictGA documentation built on May 7, 2019, 12:03 p.m.