# Augmenting Massively Parallel Cytometry Experiments Using Multivariate Non-Linear Regressions

## Documentation for package ‘infinityFlow’ version 1.2.0

- DESCRIPTION file.
- User guides, package vignettes and other documentation.

## Help Pages

fitter_glmnet | Wrapper to glmnet. Defined separetely to avoid passing too many objects in parLapplyLB
fitter_linear | Wrapper to linear model training. Defined separetely to avoid passing too many objects in parLapplyLB
fitter_nn | Wrapper to Neural Network training. Defined separetely to avoid passing too many objects in parLapplyLB
fitter_svm | Wrapper to SVM training. Defined separetely to avoid passing too many objects in parLapplyLB
fitter_xgboost | Wrapper to XGBoost training. Defined separetely to avoid passing too many objects in parLapplyLB
infinity_flow | Wrapper to the Infinity Flow pipeline
select_backbone_and_exploratory_markers | For each parameter in the FCS files, interactively prompts whether it is part of the Backbone, the Infinity (exploratory) markers or should be ignored.
steady_state_lung | Subset of a massively parallel cytometry experiment of mouse lung single cells
steady_state_lung_annotation | Target and isotypes annotation for the data object infinityFlow::steady_state_lnug
steady_state_lung_backbone_specification | Backbone and Infinity antibodies specification for the data object infinityFlow::steady_state_lnug