Package index • smartid

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

Reference

All functions