All functions

cal_score()

calculate combined score

cal_score_init()

Calculate score for each feature in each cell

gs_score()

compute overall score based on the given marker list

gs_score_init()

Calculate scores of each cell on given features

iae()

standard inverse average expression

iae_hdb()

inverse average expression using hdbscan cluster as label

iae_igm()

labeled inverse average expression: IGM

iae_m()

inverse average expression: max

iae_prob()

labeled inverse average expression: probability based

iae_rf()

labeled inverse average expression: relative frequency

iae_sd()

inverse average expression using standard deviation (SD)

idf()

standard inverse cell frequency

idf_hdb()

inverse document frequency using hdbscan cluster as label

idf_iae_methods()

Get names of available IDF and IAE methods

idf_igm()

labeled inverse cell frequency: IGM

idf_m()

inverse cell frequency: max

idf_prob()

labeled inverse cell frequency: probability based

idf_rf()

labeled inverse cell frequency: relative frequency

idf_sd()

inverse cell frequency using standard deviation (SD)

markers_hdbscan()

select markers using HDBSCAN method

markers_mclust()

select markers using mclust EM method

markers_mixmdl()

select markers using mixtools EM method

ova_score_boxplot()

boxplot of features overall score

scale_mgm()

scale by mean of group mean for imbalanced data

score_barplot()

barplot of processed score

sim_sce_test

scRNA-seq test data of 4 groups simulated by splatter.

sin_score_boxplot()

boxplot of split single feature score

tf()

compute term/feature frequency within each cell

top_markers()

scale score and return top markers

top_markers_abs()

calculate group median, MAD or mean score and order genes based on scores

top_markers_glm()

calculate group mean score using glm and order genes based on scores difference

top_markers_init()

compute group summarized score and order genes based on processed scores