ParameterConfig

The settings of an analysis: the names of the columns of the cell and bin metadata and the parameters of every step of the workflow.

Value

An object of class ParameterConfig: the settings of an analysis, one value per slot. Every step of the workflow records the settings it used in the Parameters slot of a ScMaSigPro object, and showParams() lists them.

Details

validObject() checks that every slot except distribution holds a single non-missing value, that min_counts and min_bins_expressed are at least 0, that test is "chisq" or "F" and that distribution is a stats::family() object.

Slots

bin_ptime_col: The column of the bin metadata with the binned pseudotime.
path_prefix: The default path column of as_scmp().
root_label: The label of the root cells given to as_scmp(), kept for reference.
ptime_col: The column of the cell metadata with the pseudotime.
bin_method: The rule for the number of bins of sc.squeeze().
path_col: The column of the cell and bin metadata with the path labels.
bin_col: The column of the bin metadata with the bin names.
bin_size_col: The column of the bin metadata with the number of cells of each bin.
bin_mem_col: The column of the bin metadata with the cells of each bin.
anno_col: The column of the cell metadata with cell annotations; not used by the steps.
g: The number of genes that sc.p.vector() fitted: those left after removing the genes with fewer than min_na values, with zero counts in every bin, or below min_counts or min_bins_expressed.
p_value: The level of sc.p.vector() and sc.t.fit().
min_na: The minimum number of bins with a value (not NA) that sc.p.vector() required; it only removes genes from counts with missing values.
mt_correction: The multiple-testing correction of sc.p.vector().
link: The link function of the fits.
epsilon: The convergence tolerance of the fits.
selection_method: The stepwise method of sc.t.fit().
offset: Whether the fits used the offset of each bin, the logarithm of its size factor (see sc.p.vector()).
max_it: The maximum number of iterations of the fits.
poly_degree: The degree of the polynomial of sc.set.poly().
distribution: The family of the fits, a stats::family() object; with an estimated theta it also holds theta_estimate and theta_gene (see sc.p.vector()).
cluster_method: The clustering method of sc.cluster.trend().
use_dim: How sc.cluster.trend() filled missing values: by column or by row.
fill_na: What sc.cluster.trend() filled missing values with.
min_counts: The minimum total count over the bins that sc.p.vector() required of a gene (0: no minimum).
min_bins_expressed: The minimum number of bins with a count above 0 that sc.p.vector() required of a gene (0: no minimum).
test: The test of the full model of each gene that sc.p.vector() was asked for: "chisq", the chi-squared test, or "F", the F test.

Examples

data("scmp.ob", package = "scMaSigPro")
showParams(scmp.ob)
#>            parameters                  value
#> 1       bin_ptime_col scmp_binned_pseudotime
#> 2         path_prefix                   Path
#> 3          root_label                   root
#> 4           ptime_col             Pseudotime
#> 5    selection_method               backward
#> 6          bin_method                Sturges
#> 7            path_col                   Path
#> 8             bin_col               scmp_bin
#> 9        bin_size_col          scmp_bin_size
#> 10        bin_mem_col       scmp_bin_members
#> 11           anno_col              cell_type
#> 12                  g                    100
#> 13            p_value                   0.05
#> 14             min_na                      6
#> 15      mt_correction                     BH
#> 16               link                    log
#> 17            epsilon                  1e-08
#> 18             offset                   TRUE
#> 19             max_it                    100
#> 20        poly_degree                      1
#> 21     cluster_method                 hclust
#> 22            use_dim                    col
#> 23            fill_na                   zero
#> 24         min_counts                      0
#> 25 min_bins_expressed                      0
#> 26               test                  chisq
#> 27       distribution  Negative Binomial(10)

Value

Details

Slots

See also

Examples