Myeloid Subcluster DEGs: Single-Cell RNA Sequencing of Human Milk Immune Cells

Single-cell RNA sequencing data from over 23,000 CD45+ enriched cells collected from 9 healthy lactating donors. The dataset, authored by Nadine Schrode and last updated in May 2026, identifies 18 transcriptionally distinct mononuclear myeloid subpopulations, including macrophage, dendritic cell, monocyte, and epithelial-like clusters. It includes differential gene expression analysis and pathways related to lipid adaptation and intercellular communication.

Use Cases

• Identify myeloid cell subpopulations based on transcriptional profiles described in the dataset.
• Analyze donor-specific heterogeneity in immune cell composition during lactation.
• Study gene expression pathways related to adaptation to lipid-rich environments, such as LDL clearance.
• Investigate intercellular communication networks among immune subsets using inferred signaling pathways.
• Compare M1-like and M2-like macrophage transcriptional states within human milk.

Strengths

• Data from over 23,000 cells provides a substantial sample for single-cell analysis.
• Includes cells from 9 donors, allowing for observation of inter-individual variation.
• Clustering identified 18 distinct myeloid subpopulations, offering high-resolution categorization.
• Analysis includes pathway (Reactome) and cell-cell communication (CellChat) data beyond basic expression.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Data may reflect bias inherent to the specific cohort of 9 healthy lactating donors.

Provenance

Source

figshare

Collection Method

Single-cell RNA sequencing (scRNAseq) on CD45+ enriched cells from human milk samples.

Freshness

Last updated 2026-05-11 17:35:39