A complete analysis of single cell subpopulations, from identifying subpopulations to analysing their relationship (scGPS = single cell Global Predictions of Subpopulation)

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Documentation for package ‘scGPS’ version 1.6.0

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add_import add_import
annotate_clusters annotate_clusters functionally annotates the identified clusters
bootstrap_parallel BootStrap runs for both scGPS training and prediction with parallel option
bootstrap_prediction BootStrap runs for both scGPS training and prediction
calcDist Compute Euclidean distance matrix by rows
calcDistArma Compute Euclidean distance matrix by rows
clustering HC clustering for a number of resolutions
clustering_bagging HC clustering for a number of resolutions
CORE_bagging Main clustering SCORE (CORE V2.0) Stable Clustering at Optimal REsolution with bagging and bootstrapping
CORE_clustering Main clustering CORE V2.0 updated
CORE_subcluster sub_clustering (optional) after running CORE 'test'
day_2_cardio_cell_sample One of the two example single-cell count matrices to be used for training 'scGPS' model
day_5_cardio_cell_sample One of the two example single-cell count matrices to be used for 'scGPS' prediction
distvec Compute Distance between two vectors
find_markers find marker genes
find_optimal_stability Find the optimal cluster
find_stability Calculate stability index
mean_cpp Calculate mean
new_scGPS_object new_scGPS_object
new_summarized_scGPS_object new_summarized_scGPS_object
PCA PCA
plot_CORE Plot dendrogram tree for CORE result
plot_optimal_CORE plot one single tree with the optimal clustering result
plot_reduced plot reduced data
predicting Main prediction function applying the optimal ElasticNet and LDA models
PrinComp_cpp Principal component analysis
rand_index Calculate rand index
rcpp_Eucl_distance_NotPar Function to calculate Eucledean distance matrix without parallelisation
rcpp_parallel_distance distance matrix using C++
reformat_LASSO summarise bootstrap runs for Lasso model, from 'n' bootstraps
subset_cpp Subset a matrix
sub_clustering sub_clustering for selected cells
summary_accuracy get percent accuracy for Lasso model, from 'n' bootstraps
summary_deviance get percent deviance explained for Lasso model, from 'n' bootstraps
summary_prediction_lasso get percent deviance explained for Lasso model, from 'n' bootstraps
summary_prediction_lda get percent deviance explained for LDA model, from 'n' bootstraps
top_var select top variable genes
tp_cpp Transpose a matrix
training Main model training function for finding the best model that characterises a subpopulation
training_gene_sample Input gene list for training 'scGPS', e.g. differentially expressed genes
tSNE tSNE
var_cpp Calculate variance