scClassify: Train and test scClassify model

Description Usage Arguments Value Author(s)

View source: R/scClassify.R

Description

Train and test scClassify model

Usage

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scClassify(exprsMat_train = NULL, cellTypes_train = NULL,
  exprsMat_test = NULL, cellTypes_test = NULL, tree = "HOPACH",
  algorithm = "WKNN", selectFeatures = "limma",
  similarity = "pearson", cutoff_method = c("dynamic", "static"),
  weighted_ensemble = FALSE, k = 10, topN = 50, hopach_kmax = 5,
  pSig = 0.01, prob_threshold = 0.7, cor_threshold_static = 0.5,
  cor_threshold_high = 0.7, parallel = FALSE, ncores = 1,
  verbose = FALSE)

Arguments

exprsMat_train

A matrix of expression matrix of training dataset

cellTypes_train

A vector of cell types of training dataset

exprsMat_test

A list or a matrix indicates the expression matrices of the testing datasets

cellTypes_test

A list or a vector indicates cell types of the testing datasets (Optional).

tree

A vector indicates the method to build hierarchical tree, set as "HOPACH" by default. This should be one of "HOPACH" and "HC" (using hclust).

algorithm

A vector indicates the KNN method that are used, set as "WKNN" by default. This should be one or more of "WKNN", "KNN", "DWKNN".

selectFeatures

A vector indicates the method to select features, set as "limma" by default. This should be one or more of "limma", "DV", "DD", "chisq", "BI".

similarity

A vector indicates the similarity measure that are used, set as "pearson" by default. This should be one or more of "pearson", "spearman", "cosine", "jaccard", "kendall", "binomial", "weighted_rank","manhattan"

cutoff_method

A vector indicates the method to cutoff the correlation distribution. Set as "dynamic" by default.

weighted_ensemble

A logical input indicates in ensemble learning, whether the results is combined by a weighted score for each base classifier.

k

An integer indicates the number of neighbour

topN

An integer indicates the top number of features that are selected

hopach_kmax

An integer between 1 and 9 specifying the maximum number of children at each node in the HOPACH tree.

pSig

A numeric indicates the cutoff of pvalue for features

prob_threshold

A numeric indicates the probability threshold for KNN/WKNN/DWKNN.

cor_threshold_static

A numeric indicates the static correlation threshold.

cor_threshold_high

A numeric indicates the highest correlation threshold

parallel

A logical input indicates whether running in paralllel or not

ncores

An integer indicates the number of cores that are used

verbose

A logical input indicates whether the intermediate steps will be printed

Value

A list of results including

Author(s)

Yingxin Lin


SydneyBioX/scdney documentation built on Aug. 22, 2019, 10:55 a.m.