Augmenting Massively Parallel Cytometry Experiments Using Multivariate Non-Linear Regressions

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Documentation for package ‘infinityFlow’ version 1.12.0

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

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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