Supplementary Figures: Single-Cell T-Cell Data from Lung Cancer Patients

Supplementary figures for a study analyzing single-cell RNA sequencing data from 8 lung cancer patients and 34 non-small cell lung cancer patients. The data includes gene expression patterns across 27 cell clusters and machine learning classification of T-cell subtypes. The dataset was authored by Hiroshi Kagamu and last updated on 2026-05-23.

Use Cases

• Classifying Th1, Th7R, and Th17 T-cell subtypes based on 58 signature genes using a trained SVM model.
• Analyzing gene expression patterns across 27 cell clusters from lung cancer patient samples.
• Evaluating feature importance for T-cell classification using SVM-RFE on 64 gene expression features.
• Comparing single-cell RNA-seq profiles between peripheral blood and tumor-infiltrating lymphocytes.

Strengths

• Includes data from 8 lung cancer patients and 34 non-small cell lung cancer patients.
• Uses a trained SVM model for subtype prediction based on 58 signature genes.
• Compares data across multiple cancer types, including melanoma and renal cell cancer.

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.

Provenance

Source

figshare

Collection Method

Single-cell RNA sequencing of peripheral blood and tumor-infiltrating lymphocytes from lung cancer patients.

Freshness

Last updated 2026-05-23 07:02:17; freshness should be verified.