dataColon: Contains four R-objects, including the data and the binary...

In gren: Adaptive Group-Regularized Logistic Elastic Net Regression

Description

The four objects are: mirCol: 2114 sequenced microRNAs for 88 samples; unpenCol: 4 clinical covariates for 88 samples; respCol: binary response coded as progressive disease and benefitted from therapy; mirExpr: expression levels of microRNAs from previous study coded as not differentially expressed, medium significantly expressed, and highly significantly expressed.

Usage

data(dataColon)

Format

The formats are:

mirCol

matrix [1:88, 1:2114]

unpenCol

data.frame: 88 obs. of 4 variables

respCol

Factor w/ 2 levels "Progr","TherBenefit"

mirExpr

Factor w/ 3 levels "nonExpr", "medExpr", "highExpr"

Details

This data is used for illustration in the vignette of the gren package and the corresponding paper (see references).

Source

Neerincx, M., Poel, D., Sie, D.L.S., van Grieken, N.C.T., Shankaraiah, R.C., van der Wolf - de Lijster, F.S.W., van Waesberghe, J.H.T.M., Burggraaf, J.D., Eijk, P.P., Verhoef, C., Ylstra, B., Meijer, G.A., van de Wiel, M.A., Buffart, T.E., and others. (2018). Combination of a six microRNA expression profile with four clinicopathological factors improves response prediction to systemic treatment in patients with advanced colorectal cancer. Submitted.

Neerincx, M., Sie, D.L.S., van de Wiel, M.A., van Grieken, N.C.T., Burggraaf, J.D., Dekker, H., Eijk, P.P., Ylstra, B., Verhoef, C., Meijer, G.A., Buffart, T.E., and others. (2015). MiR expression profiles of paired primary colorectal cancer and metastases by next-generation sequencing. Oncogenesis, 4, e170.

References

Münch, M.M., Peeters, C.F.W., van der Vaart, A.W., and van de Wiel, M.A. (2018). Adaptive group-regularized logistic elastic net regression. arXiv:1805.00389v1 [stat.ME].

Examples

data(dataColon)
str(mirCol)
str(unpenCol)
str(respCol)
str(mirExpr)

gren documentation built on May 1, 2019, 7:31 p.m.