ti_stemnet: STEMNET

Description Usage Arguments Value References

Description

Will generate a trajectory using STEMNET.

This method was wrapped inside a container. The original code of this method is available here.

Usage

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ti_stemnet(alpha = 0.1, lambda_auto = TRUE, lambda = 0.1,
  force = FALSE)

Arguments

alpha

The elastic net mixing parameter of the ‘glmnet’ classifier. Domain: e^U(-6.91, 2.30). Default: 0.1. Format: numeric.

lambda_auto

Whether to select the lambda by cross-validation. Default: TRUE. Format: logical.

lambda

The lambda penalty of GLM. Domain: e^U(-3.00, 0.00). Default: 0.1. Format: numeric.

force

Do not use! This is a parameter to force STEMNET to run on benchmark datasets where not enough end groups are present. Default: FALSE. Format: logical.

Value

A TI method wrapper to be used together with infer_trajectory

References

Velten, L., Haas, S.F., Raffel, S., Blaszkiewicz, S., Islam, S., Hennig, B.P., Hirche, C., Lutz, C., Buss, E.C., Nowak, D., Boch, T., Hofmann, W.-K., Ho, A.D., Huber, W., Trumpp, A., Essers, M.A.G., Steinmetz, L.M., 2017. Human haematopoietic stem cell lineage commitment is a continuous process. Nature Cell Biology 19, 271–281.


dynverse/dynmethods documentation built on July 6, 2019, 11:30 a.m.