tm_facs_logistic: tm_facs_logistic

In hemberg-lab/sctransfermap: sctransfermap for predicting cell type in single-cell data (RNA-seq and ATAC-seq)

Description

prediction by logistic regression for multiple data

Usage

tm_facs_logistic(att_set, meta_model, sig_set, Tissue_opt = FALSE,
  celltype_specific = FALSE)

Arguments

att_set	attribute set
meta_model	logistic regression model from create_meta_index_av
sig_set	signature set
Tissue_opt	TRUE if user wants to find tissue-origin
celltype_specific	TRUE if user wants to calculate the weight fo each tissue with only matched cell type. Otherwise, weight for each tissue will be calculated with whole celltypes (deault: FALSE; tissue_opt should be TRUE to use this parameter)

Value

6 results: conf_list, conf_ratio_list, val_list, tissue_list, f1_list, unassign_list

• conf_list: confusion matrix

• conf_ratio_list: ratio_list (confusion_ratio_matrix)

• val_list: validation matrix

• tissue_list

• f1_list: f1 score

• unassign_list

- each result is composed of sample in TM (ex: res$conf_list[1]: confusion matrix of Aorta tissue)

Examples

meta_model <- create_meta_index_av(att_set1, sig_set1)
res <- tm_facs_logistic(att_set1, meta_model, sig_set2)

hemberg-lab/sctransfermap documentation built on Nov. 11, 2019, 6:23 a.m.