Interpretation of DNA methylation data from tumour samples using XGBoost models. The methXGB package contains a collection of trained models and wrapper functions that facilitate their use.
library(devtools)
install_github("translational-genomics-laboratory/methXGB")
Model family | No. models | Model class | Training dataset | Data type (features) | Dependent variable (target) |
---|---|---|---|---|---|
immunescore | 20 | XGBoost_reg:linear | TCGA various tumour types | M-values from 450k DNA methylation array | ESTIMATE.immunescore array |
purity | 20 | XGBoost_reg:linear | TCGA various tumour types | M-values from 450k DNA methylation array | InfiniumPurify |
- The function
inferMethXGB()
is used to infer biological parameters in DNA methylation data by using one of the trained XGBoost models included in the methXGB package. For example, the commandinferMethXGB(mval=mval_demo, model.family="purity",dataset="GBMLGG")
is used to infer tumour purity using DNA methylation from the examplemval_demo
data frame containing M-values. - The
idatParse()
functon extracts M-values from idat files (450k and EPIC platforms). It provides readily access to data in M-values format, but it is not a replacement for cumstom-built workflows. getModelInfo()
returns the description of the models that are included in the methXGB package.
Developed by Alberto León at the PM-OICR Translational Genomics Laboratory