Get dynamic genes
dynamic_genes(object, ...)
# S4 method for class 'matrix'
dynamic_genes(
object,
pseudotime = NULL,
cores = 1,
verbose = TRUE,
adjust_method = "BH",
...
)
# S4 method for class 'Seurat'
dynamic_genes(
object,
pseudotime_column,
cores = 1,
verbose = TRUE,
adjust_method = "BH",
layer = "data",
...
)
The input data, a matrix with cells/samples by genes/features or a seurat object.
Arguments for other methods
Pseudotime of cells, the length and order should be the same as the expression matrix columns.
The number of cores to use for parallelization with foreach
, default is 1
.
Logical value, default is TRUE
, whether to print progress messages.
The method used to calculate adjust P-value.
The column name in meta_data annotating pseudotime or latent time.
The layer used in Seurat object.
A new object with dynamic genes
data("example_matrix")
data("example_meta_data")
dynamic_genes(
object = example_matrix,
pseudotime = example_meta_data$pseudotime
)
#> ℹ [2025-05-28 02:34:53] Using 1 core
#> gene p_value adjust_p_value
#> 2 g10 0.000000e+00 0.000000e+00
#> 3 g11 0.000000e+00 0.000000e+00
#> 4 g12 0.000000e+00 0.000000e+00
#> 5 g13 0.000000e+00 0.000000e+00
#> 6 g14 0.000000e+00 0.000000e+00
#> 7 g15 0.000000e+00 0.000000e+00
#> 8 g16 0.000000e+00 0.000000e+00
#> 9 g17 0.000000e+00 0.000000e+00
#> 10 g18 0.000000e+00 0.000000e+00
#> 13 g4 0.000000e+00 0.000000e+00
#> 14 g5 0.000000e+00 0.000000e+00
#> 15 g6 0.000000e+00 0.000000e+00
#> 16 g7 0.000000e+00 0.000000e+00
#> 17 g8 0.000000e+00 0.000000e+00
#> 18 g9 0.000000e+00 0.000000e+00
#> 12 g3 1.333076e-178 1.499711e-178
#> 1 g1 1.185038e-119 1.254746e-119
#> 11 g2 8.676800e-01 8.676800e-01
if (FALSE) { # \dontrun{
vector_result <- infer_vector(example_matrix)
dynamic_genes(
object = vector_result$matrix,
pseudotime = vector_result$pseudotime[, 2]
)
} # }