compute_power: Computing Power for Single Cell Expression Case-Control...

In kdzimm/hierarchicell: Simulating Cell-Type Specific and Hierarchical Single-Cell RNA-Seq Data

Description

Computes power for single cell data that is cell-type specifc and hierarchical. This function computes power using random effects to account for the correlation structure that exists among measures from cells within an individual. The power 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.

Details

Prior to running the power_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.

Note

Data should be only for cells of the specific cell-type you are interested in simulating or computing power 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.

kdzimm/hierarchicell documentation built on Dec. 21, 2021, 5:23 a.m.