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Get Residuals For Highly Variable Genes

Source: R/hvgs.R
topHVGs.Rd

Extract residuals for top n highly variable genes

Usage

topHVGs(x, fit, n = nrow(x))

Arguments

x

ResidualMatrixGLM matrix

fit

model fit from lucida()

n

number of genes to extract

See also

findHVGs()

Examples

library(SingleCellExperiment)

# Load example data
data(example_sce, package="muscat")
sce <- example_sce

# Compute library size for each cell
sce$libSize <- colSums(counts(sce))

# fit joint model on all cells
fit <- lucida(sce, ~ 1)
#> Analyze all cells jointly...
#> all 
#> 
  |                                                              |   0%, ETA NA
  |=======================================================| 100%, Elapsed 00:01
#> 
  |                                                              |   0%, ETA NA
  |=======================================================| 100%, Elapsed 00:00
#> 

# extract residuals as a ResidualMatrixGLM
res <- residuals(fit, sce)

# Extract top 100 highly variables genes
topHVGs( res, fit, 100)
#> <100 x 1556> DelayedMatrix object of type "double":
#>        ATCATGCTGCGTAT-1 GTACGAACTGTCAG-1 ... TCAAGGTGGAATGA-1 GAATGGCTAAACAG-1
#>   FTH1        19.583616        12.068644   .        38.588972        38.312189
#> MALAT1        22.063063        27.029746   .        33.867262        53.946640
#>    B2M        17.905081        16.172044   .        26.076119        47.126060
#>    FTL         3.729061         1.945190   .         4.945306        11.284633
#> TMSB4X         5.838556         9.095312   .        24.693523        37.767697
#>    ...                .                .   .                .                .
#>  RPL18       6.71501636       6.71501636   .      -0.06890475       5.73855468
#>  IFIT3      -0.06052771      -0.06052771   .      14.37607837      15.08728053
#>   RPS5      -0.06918068       6.64209215   .       5.68144382       8.25281526
#> IFITM3      -0.05633518      -0.05633518   .      11.33393261      11.73624188
#>  ANXA2      -0.05229725      -0.05229725   .       9.32236380       6.93187352