find marker genes — find_markers • scGPS

Find DE genes from comparing one clust vs remaining

find_markers(
  expression_matrix = NULL,
  cluster = NULL,
  selected_cluster = NULL,
  fitType = "local",
  dispersion_method = "per-condition",
  sharing_Mode = "maximum"
)

Arguments

expression_matrix	is a normalised expression matrix.
cluster	corresponding cluster information in the expression_matrix by running CORE clustering or using other methods.
selected_cluster	a vector of unique cluster ids to calculate
fitType	string specifying 'local' or 'parametric' for DEseq dispersion estimation
dispersion_method	one of the options c( 'pooled', 'pooled-CR', per-condition', 'blind' )
sharing_Mode	one of the options c("maximum", "fit-only", "gene-est-only")

Value

a list containing sorted DESeq analysis results

Author

Quan Nguyen, 2017-11-25

Examples

day2 <- day_2_cardio_cell_sample
mixedpop1 <-new_scGPS_object(ExpressionMatrix = day2$dat2_counts, 
    GeneMetadata = day2$dat2geneInfo, CellMetadata = day2$dat2_clusters)
# depending on the data, the DESeq::estimateDispersions function requires
# suitable fitType
# and dispersion_method options
DEgenes <- find_markers(expression_matrix=assay(mixedpop1),
                        cluster = colData(mixedpop1)[,1],
                        selected_cluster=c(1), #can also run for more
                        #than one clusters, e.g.selected_cluster = c(1,2)
                        fitType = "parametric", 
                        dispersion_method = "blind",
                        sharing_Mode="fit-only"
                        )
#> converting counts to integer mode
#> gene-wise dispersion estimates
#> mean-dispersion relationship
#> -- note: fitType='parametric', but the dispersion trend was not well captured by the
#>    function: y = a/x + b, and a local regression fit was automatically substituted.
#>    specify fitType='local' or 'mean' to avoid this message next time.
#> final dispersion estimates
names(DEgenes)
#> [1] "baseMean"       "log2FoldChange" "lfcSE"          "stat"          
#> [5] "pvalue"         "padj"           "id"