This dataset contains transcriptome expression data from 7,930 single cells, covering three different biological states: healthy immune baseline, liquid tumor (myeloid leukemia), and solid tumor microenvironment (melanoma). It aims to build a cross-cohort integrated single-cell analysis benchmark to provide a benchmark for algorithm performance evaluation and methodological comparison, multi-cohort batch effect correction, immune exhaustion state analysis, and cross-tumor type biomarker mining.

Dataset composition:
1. Cohort A: Healthy immune baseline (approximately 2,700 cells)

• Source: 10x Genomics PBMC3k
• Biological background: Peripheral blood mononuclear cells (PBMCs) from healthy donors were used as a baseline control for immune homeostasis.
• Purpose: To compare changes in tumor-associated immune status.

2. Cohort B: Liquid tumor/myeloid leukemia (approximately 2,730 cells)

• Source: Paul et al., 2015
• Biological background: Single-cell transcriptome data of myeloid progenitor cells and leukemia-related cell states
• Function: Represents a model of hematologic malignancies

3. Cohort C: Solid tumor microenvironment (approximately 2,500 cells)

• Source: Tumor Immune Cell Atlas (TICAtlas)
• Biological background: Immune cells and malignant cells originating from the microenvironment of solid tumors such as melanoma, including exhausted T cells, macrophages, and tumor cells.
• Application: Used to study immunosuppression and cellular heterogeneity in solid tumors.