no_significance_df: no_significance_df

In stemangiola/sccomp: Robust Outlier-aware Estimation of Composition and Heterogeneity for Single-cell Data

no_significance_df

Description

A small example dataset containing cell counts across samples, conditions, and cell groups. This dataset is used to demonstrate the use of sccomp functions in scenarios where there is no significant difference in cell composition between conditions.

Usage

data(no_significance_df)

Format

A tibble with the following columns:

• sample: Character. Identifier for each sample.

• condition: Character. Experimental condition or group (e.g., "X" or "Y").

• cell_group: Character. Cell group or cell type (e.g., "A", "B").

• count: Numeric. Count of cells in the given sample, condition, and cell group.

Value

A tibble with 34 rows and 4 columns: sample, condition, cell_group, and count.

Examples

data(no_significance_df)
head(no_significance_df)

stemangiola/sccomp documentation built on Dec. 20, 2024, 8:38 a.m.