Computes type 1 error for single cell data that is cell-type specifc, hierarchical, and compositonal. This function computes type 1 error with the single-cell differential expression analysis tool 'MAST', using random effects to account for the correlation structure that exists among measures from cells within an individual. The type 1 error calculations will borrow information from the input data (or the package default data) to simulate data under a variety of pre-determined conditions. These conditions include foldchange, number of genes, number of samples (i.e., independent experimental units), and the mean number of cells per individual.
Prior to running the error_hierarchicell
function, it
is important to run the filter_counts
function followed by
the compute_data_summaries
function to build an R object that
is in the right format for the following simulation function to properly
work.
Data should be only for cells of the specific cell-type you are interested in simulating or computing type 1 error for. Data should also contain as many unique sample identifiers as possible. If you are inputing data that has less than 5 unique values for sample identifier (i.e., independent experimental units), then the empirical estimation of the inter-individual heterogeneity is going to be very unstable. Finding such a dataset will be difficult at this time, but, over time (as experiments grow in sample size and the numbers of publically available single-cell RNAseq datasets increase), this should improve dramatically.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.