How do I access the
scale_sampler method? For a given cell type, I would like to compute the
scale1 value (the normalized expression) that is reported from
For example, let's say I want to get the normalized expression of all genes on the ASK neurons. Right now, I can do that by doing:
de = model.differential_expression(group1='ASK',group2='ASJ',groupby='cell_type') ASK_normalized_expression= de['scale1']
However this takes ~10s and is computing a bunch of other things that I don't need. I want to build a matrix of the normalized expression for all cell types (150 cell types x 11k genes) so doing this 150 times takes ~25 min and I'd want to make it quicker if possible..
scale_sampler is described here:
normalized_expression_matrix = model.get_normalized_expression(batch_size=1000)but still crashes... the adata is
n_obs × n_vars = 100955 × 11569, other than getting more RAM is there something I could do to get this to run on colab?