Calculate basic statistics on a matrix

scm_gene_stat(
  mat_id,
  niche_quantile = 0.2,
  downsample_n = NULL,
  K_std_n = 1000
)

Arguments

niche_quantile: A value between 0 and 1.
mat: The input matrix

Value

Returns a dataset that contains statistic for all genes that passed the filtering stage. Columns starting with ds contain UMI statistics after downsampling, columns starting with n contain UMI statistics after normalizing UMIs so that the number of UMIs per cell sums to 1. The columns are:

tot: Total gene expression
var: Gene variance
is_on_count: Number of cells in which the gene is expressed
sz_cor: Correlation with cell size
sz_cor_norm: sz_cor after subtracting the trend
niche_stat: How many of the genen's umis are found in X% of the most highly expressing cells. (regularized)
niche_norm: niche_stat after subtracting the niche_norm trend: median niche_norm value of genes with similar total expression
n_mean: Mean after normalization
ds_top1: Largest count, after downsampling
ds_top2: 2nd largest count, after downsampling
ds_top3: 3rd largest count, after downsampling
ds_mean: Mean on downsampled data
ds_var: Variance on downsampled data
ds_log_varmean: log2 of ds_var/ds_mean
ds_vm_norm: ds_log_varmean after subtracting the trend
ds_is_on_count: Number of cells in which the gene is expressed, after down sampling
downsample_n: Number of UMIs used for downsampling