Differentially Expressed Genes in CD1D Knockout Vaccination Study

Figshare hosts a dataset of differentially expressed genes from a vaccination challenge study comparing CD1D knockout (G1) and wild-type (G2) mice across cell types. Author Taeyong Kwon published the data in April 2026 to support findings related to a specific figure. The dataset is a 1.8 MB CSV file.

Use Cases

• Identify cell-type-specific gene expression changes between CD1D -/- and CD1D -/+ conditions using log fold change and p-value columns.
• Validate immunological hypotheses from the related publication by analyzing lists of up- and down-regulated genes per cell type.
• Perform pathway enrichment analysis on the sets of differentially expressed genes to understand affected biological processes.
• Compare gene expression signatures from this knockout model with other vaccination or infection datasets.

Strengths

• Dataset is openly licensed under CC-BY-4.0 for clear reuse.
• Data is directly linked to a specific published figure (Fig 6) for contextual validation.
• File size of 1.8 MB indicates a processed, analysis-ready table.

Limitations

• The small 1.8 MB file size suggests a limited number of rows or features, potentially a summary table rather than raw data.
• Unknown row count and absence of column details prevent assessment of data completeness and feature scope.
• Lack of sample data or column descriptions makes initial exploration and schema understanding difficult.

Provenance

Source

Figshare, authored by Taeyong Kwon.

Collection Method

Likely derived from single-cell RNA sequencing analysis of mouse samples following vaccination and challenge.

Freshness

Last updated on 2026-04-06.