multi_beta_binomial_glm: multi_beta_binomial main

In stemangiola/sccompTemp: Outlier-aware and Count-based Compositional Analysis of Single-cell Data.

Description

This function runs the data modelling and statistical test for the hypothesis that a cell_type includes outlier biological replicate.

Usage

multi_beta_binomial_glm(
  .data,
  formula = ~1,
  .sample,
  .cell_type,
  .count,
  check_outliers = FALSE,
  approximate_posterior_inference = T,
  variance_association = F,
  cores = detectCores(),
  seed = sample(1:99999, size = 1),
  verbose = FALSE
)

Arguments

.data	A tibble including a cell_type name column | sample name column | read counts column | covariate columns | Pvaue column | a significance column
formula	A formula. The sample formula used to perform the differential cell_type abundance analysis
.sample	A column name as symbol. The sample identifier
.cell_type	A column name as symbol. The cell_type identifier
.count	A column name as symbol. The cell_type abundance (read count)
approximate_posterior_inference	A boolean. Whether the inference of the joint posterior distribution should be approximated with variational Bayes. It confers execution time advantage.
cores	An integer. How many cored to be used with parallel calculations.
seed	An integer. Used for development and testing purposes

Value

A nested tibble tbl with cell_type-wise information: sample wise data | plot | ppc samples failed | exposure deleterious outliers

stemangiola/sccompTemp documentation built on Dec. 23, 2021, 5:30 a.m.