FEAture SelcTion (FEAST) for Single-cell clustering

Documentation for package ‘FEAST’ version 1.8.0

align_CellType	Align the cell types from the prediction with the truth.
cal_F2	Calculate the gene-level F score and corresponding significance level.
cal_Fisher2	Calculate the gene-level fisher score.
cal_metrics	Calculate 3 metrics and these methods are exported in C codes. flag = 1 - Rand index, flag = 2 - Fowlkes and Mallows's index, flag = 3 - Jaccard index
cal_MSE	Standard way to preprocess the count matrix. It is the QC step for the genes.
Consensus	Consensus Clustering
eval_Cluster	Calculate the a series of the evaluation statistics.
FEAST	FEAST main function
FEAST_fast	FEAST main function (fast version)
Norm_Y	Normalize the count expression matrix by the size factor and take the log transformation.
process_Y	Standard way to preprocess the count matrix. It is the QC step for the genes.
Purity	Calculate the purity between two vectors.
SC3_Clust	SC3 Clustering
Select_Model_short_SC3	Using clustering results based on feature selection to perform model selection.
Select_Model_short_TSCAN	Using clustering results (from TSCAN) based on feature selection to perform model selection.
trueclass	An example single cell dataset for the cell label information (Yan)
TSCAN_Clust	TSCAN Clustering
vector2matrix	function for convert a vector to a binary matrix
Visual_Rslt	Using clustering results based on feature selection to perform model selection.
Y	An example single cell count expression matrix (Yan)