Computing Cepo cell identity genes

ExprsMat accepts various matrix objects, including DelayedArray and HDF5Array for out-of-memory computations. See vignette.

Cepo(
  exprsMat,
  cellTypes,
  minCells = 20,
  minCelltype = 3,
  exprsPct = 0.05,
  prefilter_sd = NULL,
  prefilter_pzero = NULL,
  logfc = NULL,
  computePvalue = NULL,
  computeFastPvalue = TRUE,
  variability = "CV",
  method = "weightedMean",
  weight = c(0.5, 0.5),
  workers = 1L,
  block = NULL,
  ...
)

Arguments

exprsMat: Expression matrix where columns denote cells and rows denote genes
cellTypes: Vector of cell type labels
minCells: Integer indicating the minimum number of cells required within a cell type
minCelltype: Integer indicating the minimum number of cell types required in each batch
exprsPct: Percentage of lowly expressed genes to remove. Default to NULL to not remove any genes.
prefilter_sd: Numeric value indicating threshold relating to standard deviation of genes. Used with prefilter_zeros.
prefilter_pzero: Numeric value indicating threshold relating to the percentage of zero expression of genes. Used with prefilter_sd.
logfc: Numeric value indicating the threshold of log fold-change to use to filter genes.
computePvalue: Whether to compute p-values using bootstrap test. Default to NULL to not make computations. Set this to an integer to set the number of bootstraps needed (recommend to be at least 100).
computeFastPvalue: Logical vector indicating whether to perform a faster version of p-value calculation. Set to TRUE by default.
variability: A character indicating the stability measure (CV, IQR, MAD, SD). Default is set to CV.
method: Character indicating the method for integration the two stability measures. By default this is set to 'weightedMean' with equal weights.
weight: Vector of two values indicating the weights for each stability measure. By default this value is c(0.5, 0.5).
workers: Number of cores to use. Default to 1, which invokes BiocParallel::SerialParam. For workers greater than 1, see the workers argument in BiocParallel::MulticoreParam and BiocParallel::SnowParam.
block: Vector of batch labels
...: Additional arguments passed to BiocParallel::MulticoreParam and BiocParallel::SnowParam.

Value

Returns a list of key genes.

Examples

library(SingleCellExperiment)
#> Loading required package: SummarizedExperiment
#> Loading required package: MatrixGenerics
#> Loading required package: matrixStats
#> 
#> Attaching package: ‘matrixStats’
#> The following objects are masked from ‘package:Biobase’:
#> 
#>     anyMissing, rowMedians
#> 
#> Attaching package: ‘MatrixGenerics’
#> The following objects are masked from ‘package:matrixStats’:
#> 
#>     colAlls, colAnyNAs, colAnys, colAvgsPerRowSet, colCollapse,
#>     colCounts, colCummaxs, colCummins, colCumprods, colCumsums,
#>     colDiffs, colIQRDiffs, colIQRs, colLogSumExps, colMadDiffs,
#>     colMads, colMaxs, colMeans2, colMedians, colMins, colOrderStats,
#>     colProds, colQuantiles, colRanges, colRanks, colSdDiffs, colSds,
#>     colSums2, colTabulates, colVarDiffs, colVars, colWeightedMads,
#>     colWeightedMeans, colWeightedMedians, colWeightedSds,
#>     colWeightedVars, rowAlls, rowAnyNAs, rowAnys, rowAvgsPerColSet,
#>     rowCollapse, rowCounts, rowCummaxs, rowCummins, rowCumprods,
#>     rowCumsums, rowDiffs, rowIQRDiffs, rowIQRs, rowLogSumExps,
#>     rowMadDiffs, rowMads, rowMaxs, rowMeans2, rowMedians, rowMins,
#>     rowOrderStats, rowProds, rowQuantiles, rowRanges, rowRanks,
#>     rowSdDiffs, rowSds, rowSums2, rowTabulates, rowVarDiffs, rowVars,
#>     rowWeightedMads, rowWeightedMeans, rowWeightedMedians,
#>     rowWeightedSds, rowWeightedVars
#> The following object is masked from ‘package:Biobase’:
#> 
#>     rowMedians
#> Loading required package: GenomicRanges
#> Loading required package: GenomeInfoDb
data('cellbench', package = 'Cepo')
cellbench
#> class: SingleCellExperiment 
#> dim: 894 895 
#> metadata(3): scPipe Biomart log.exprs.offset
#> assays(2): counts logcounts
#> rownames(894): AP000902.1 TNNI3 ... SCMH1 IGF2BP2
#> rowData names(0):
#> colnames(895): CELL_000001 CELL_000003 ... CELL_000955 CELL_000965
#> colData names(17): unaligned aligned_unmapped ... sizeFactor celltype
#> reducedDimNames(0):
#> mainExpName: NULL
#> altExpNames(0):
cepoOutput <- Cepo(logcounts(cellbench), cellbench$celltype)
cepoOutput
#> $stats
#> DataFrame with 889 rows and 3 columns
#>                H1975     H2228    HCC827
#>            <numeric> <numeric> <numeric>
#> AC092447.7  0.849162 -0.448045 -0.401117
#> CT45A3      0.831285 -0.406425 -0.424860
#> AL049870.3  0.811872 -0.463128 -0.348743
#> TDRD9       0.750559 -0.438966 -0.311592
#> TNNI3       0.745810 -0.357402 -0.388408
#> ...              ...       ...       ...
#> STK24      -0.654050  0.370391  0.283659
#> CPVL       -0.667877  0.138268  0.529609
#> BBOX1-AS1  -0.673324  0.437011  0.236313
#> COL4A2     -0.688128  0.397905  0.290223
#> KCNK1      -0.699022  0.330866  0.368156
#> 
#> $pvalues
#> NULL
#> 
#> attr(,"class")
#> [1] "Cepo" "list"