| analysis_date | h5ad_file | species | total_cells | design_type | edviz_grammar | factors | tool_version | ||||
|---|---|---|---|---|---|---|---|---|---|---|---|
2025-11-12 |
GSE166504.h5ad |
Mouse (Mus musculus) |
82192 |
Unbalanced factorial design with crossed factors |
(CellFraction(2) × DietTimepoint(4)) > Sample(38) : CellType(13) |
|
0.1.0 |
File: GSE166504.h5ad Analysis Date: 2025-11-12 Species: Mouse (Mus Musculus) Total Cells: 82,192
Experiment Type: Liver cell profiling under different diet conditions
Research Question: How do high-fat high-sugar (HFHS) diet and duration affect liver cell populations in hepatocytes vs non-parenchymal cells?
Factor Descriptions:
- Cell Fraction: Two major liver cell fractions: Hepatocytes (parenchymal cells performing metabolic functions) vs NPC (non-parenchymal cells including immune, endothelial, and stellate cells)
- Diet Timepoint: Diet conditions and duration: 15weeks, 30weeks, 34weeks on HFHS diet, and Chow (control diet). Note: Hepatocyte fraction lacks 34weeks timepoint, creating an unbalanced design
- Sample: Individual samples representing technical replicates (Captures) from biological replicates (Animals) across cell fraction and diet/time combinations. Total of 38 samples: 16 Hepatocyte samples (across 3 timepoints) and 22 NPC samples (across 4 timepoints)
- Cell Type: Cell populations identified by marker expression: immune cells (B, T, DCs, pDCs, NK, Neutrophils), liver-specific cells (Hepatocytes, Kupffer cells, Stellate cells, Hepatic progenitor cells), stromal cells (Endothelial cells, Myofibroblasts), and monocyte/macrophages
| Factor | Levels | Type |
|---|---|---|
| Cell Fraction | 2 | Treatment |
| Diet Timepoint | 4 | Treatment |
| Sample | 38 | Replicate |
| Cell Type | 13 | Observation |
This dataset exhibits a hierarchical nested design with multiple levels of nesting. Cell Types are observed across all samples, creating a crossed relationship with the nested structure.
┌──────────────────── Design Structure ────────────────────┐
│ │
│ CellFraction(2) ────×──── DietTimepoint(4) │
│ ↓ │
│ │
│ Sample(38) │
│ : │
│ │
│ CellType(13) │
│ │
└──────────────────────────────────────────────────────────┘
(CellFraction(2) × DietTimepoint(4)) > Sample(38) : CellType(13)
Samples per Cell Fraction: 16 - 22 (mean: 19)
Samples per Diet Timepoint: 2 - 12 (mean: 9)
Cells per Cell Type: 99 - 25,848 (mean: 6,322)
This design structure has implications for statistical analysis:
Random Effects Modeling: The nesting of sample within cell_fraction indicates that sample-specific variation should be modeled as a random effect. When testing for cell_fraction effects, use mixed-effects models with random intercepts for sample (e.g., ~ cell_fraction + (1|sample) in lme4 notation).
Aggregation Strategy: For differential expression testing, pseudobulking to the sample level preserves the experimental unit structure. Aggregate cells to sample-by-cell_type pseudobulk profiles before applying standard DE methods, treating samples as biological replicates.
Contrast Specification: When comparing cell_fractions, ensure contrasts are computed at the sample level, not the cell level, to avoid pseudoreplication and inflated Type I error rates.
The design is unbalanced: Hepatocyte samples lack the 34weeks timepoint (only present in NPC samples)
Samples include both biological replicates (Animals) and technical replicates (Captures), with varying numbers of captures per animal