reformat_LASSO {scGPS} | R Documentation

## summarise bootstrap runs for Lasso model, from `n` bootstraps

### Description

the training and prediction results from `bootstrap` were written to the object `LSOLDA_dat`, the `reformat_LASSO` summarises prediction for `n` bootstrap runs

### Usage

    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])
    reformat_LASSO(LSOLDA_dat=LSOLDA_dat,
        nPredSubpop=length(unique(colData(mixedpop2)[,1])), c_selectID = 1,
        mp_selectID =2, nboots = 2)

[Package scGPS version 1.2.0 Index]