summarise bootstrap runs for Lasso model, from n bootstraps

Source: R/scgps_prediction_summary.R

the 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
)

Arguments

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 row_cluster <-length(unique(target_cluster))
Nodes_group

string representation of hexidecimal color code for node
nboots

is an integer for how many bootstraps are run

Value

a dataframe containg information for the Lasso prediction results, each column contains prediction results for all subpopulations from each bootstrap run

Examples

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])

#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> done training for bootstrap 1, moving to prediction...
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> Warning: variables are collinear
#> done training for bootstrap 2, moving to prediction...
reformat_LASSO(LSOLDA_dat=LSOLDA_dat, 
    nPredSubpop=length(unique(colData(mixedpop2)[,1])), c_selectID = 1, 
    mp_selectID =2, nboots = 2)

#>          Boostrap1        Boostrap2 Target Source   Node NodeGroup    Value
#> 1 35.2941176470588 29.4117647058824 C1_MP2 C1_MP2 C1_MP2   #7570b3 32.35294
#> 2 1.42857142857143 22.8571428571429 C2_MP2 C1_MP2 C1_MP2   #7570b3 12.14286
#> 3                0 90.2255639097744 C3_MP2 C1_MP2 C1_MP2   #7570b3 45.11278
#> 4              2.5             67.5 C4_MP2 C1_MP2 C1_MP2   #7570b3 35.00000