| reformat_LASSO {scGPS} | R Documentation |
n bootstrapsthe training and prediction results from bootstrap
were written to the object LSOLDA_dat, the reformat_LASSO
summarises prediction for n bootstrap runs
reformat_LASSO(c_selectID = NULL, mp_selectID = NULL, LSOLDA_dat = NULL, nPredSubpop = NULL, Nodes_group = "#7570b3", nboots = 2)
c_selectID |
is the original cluster to be projected |
mp_selectID |
is the target mixedpop to project to |
LSOLDA_dat |
is the results from the bootstrap |
nPredSubpop |
is the number of clusters in the target mixedpop
|
Nodes_group |
string representation of hexidecimal color code for node |
nboots |
is an integer for how many bootstraps are run |
a dataframe containg information for the Lasso prediction results, each column contains prediction results for all subpopulations from each bootstrap run
c_selectID<-1
day2 <- day_2_cardio_cell_sample
mixedpop1 <-new_scGPS_object(ExpressionMatrix = day2$dat2_counts,
GeneMetadata = day2$dat2geneInfo, CellMetadata = day2$dat2_clusters)
day5 <- day_5_cardio_cell_sample
mixedpop2 <-new_scGPS_object(ExpressionMatrix = day5$dat5_counts,
GeneMetadata = day5$dat5geneInfo, CellMetadata = day5$dat5_clusters)
genes <-training_gene_sample
genes <-genes$Merged_unique
LSOLDA_dat <- bootstrap_prediction(nboots = 2, mixedpop1 = mixedpop1,
mixedpop2 = mixedpop2, genes=genes, c_selectID, listData =list(),
cluster_mixedpop1 = colData(mixedpop1)[,1],
cluster_mixedpop2=colData(mixedpop2)[,1])
reformat_LASSO(LSOLDA_dat=LSOLDA_dat,
nPredSubpop=length(unique(colData(mixedpop2)[,1])), c_selectID = 1,
mp_selectID =2, nboots = 2)