Calculate mean trajectory of clusters — calculate_mean_cluster

Function which calculates the mean trajectory of each cluster

calculate_mean_cluster_traj(clust_traj_dta)

Arguments

clust_traj_dta: gene trajectory data for each gene, obtained by calculate_cluster_traj_data

Value

A dataframe containing the mean cluster trajectories

Examples

TS_object<-create_example_object_for_R()
TS_object <- normalize_timeSeries_with_deseq2(time_object=TS_object)
#> converting counts to integer mode
#Perform conditional differential gene expression analysis
TS_object<-conditional_DE_wrapper(TS_object,vignette_run=TRUE)
TS_object<-temporal_DE_wrapper(TS_object,do_all_combinations=TRUE,vignette_run=TRUE)

#Extract genes for PART clustering based on defined log(2)foldChange threshold
signi_genes<-select_genes_with_l2fc(TS_object)

#Use all samples, but implement a custom order. In this case it is reversed
sample_data<-exp_sample_data(TS_object)
TS_groups<-slot(TS_object,'group_names')
samps_2<-sample_data$sample[sample_data$group==TS_groups[2]]
samps_1<-sample_data$sample[sample_data$group==TS_groups[1]]

#Create the matrix that will be used for PART clustering
TS_object<-prep_counts_for_PART(object=TS_object,target_genes=signi_genes,scale=TRUE,target_samples=c(samps_2,samps_1))
TS_object<-compute_PART(TS_object,part_recursion=10,part_min_clust=10,dist_param="euclidean", hclust_param="average",vignette_run=TRUE)
ts_data<-calculate_cluster_traj_data(TS_object,scale_feat=TRUE) #Calculate scaled gene values for genes of clusters
mean_ts_data<-calculate_mean_cluster_traj(ts_data) #Calculate the mean scaled values for each cluster