scLearn_cell_assignment: To predict the cell assignment result with trained scLearn...
In bm2-lab/scLearn: Learning for single cell assignment

scLearn_cell_assignment

R Documentation

To predict the cell assignment result with trained scLearn model.

To predict the cell assignment result with trained scLearn model.

scLearn_cell_assignment(scLearn_model_learning_result, expression_profile_query, vote_rate = 0.6, diff = 0.05,threshold_use=TRUE)

`scLearn_model_learning_result`	The result calculated by function "scLearn_model_learning".
`expression_profile_query`	A dataframe showing the query expression profile. The row is gene and The column is sample.
`vote_rate`	For 10 times bootstrappings, the percentage of 10 results that has the same assigned cell type. Default is 0.6. If you want a less strict assignment result for "unassigned", you can set it smaller, such as 0.5.
`diff`	For similar cell types, it is hard to distinguish. If a query cell, if its similarity value to different cell types is too close, then it will be assigned as "unassigned". Default is 0.05. If you want a less strict assignment result for "unassigned", you can set it smaller,such as 0.01.
`threshold_use`	Default is FALSE. If TRUE, the calculated thresholds to determine "unassigned" cells were used. If FALSE, the calculated thresholds to determine "unassigned" cells were not used, you will get a weak strict result.