Table 1_Integrate single-cell and transcriptome analyses to explore the prognostic genes r

A 20.5 KB dataset by Qi Zhao, last updated April 13, 2026, containing results from an integrated analysis of single-cell and whole-genome transcriptomic data for bladder cancer. The study identified 220 candidate genes and constructed a six-gene prognostic risk model, including UNC93B1, FAM193B, POGLUT3, FBN1, MAP1B, and RUNX2.

Use Cases

• Validating a six-gene prognostic risk model for bladder cancer based on the identified genes UNC93B1, FAM193B, POGLUT3, FBN1, MAP1B, and RUNX2.
• Analyzing immune infiltration patterns based on the 12 distinct immune cell types identified in the study.
• Investigating drug sensitivity differentials based on the analysis of 112 drugs, including WZ3105.
• Exploring pathway disparities in bladder cancer based on the gene set enrichment analysis results, such as the melanoma pathway.

Strengths

• Analysis identified a specific six-gene prognostic risk model (UNC93B1, FAM193B, POGLUT3, FBN1, MAP1B, RUNX2).
• Study integrated multiple data types, resulting in 220 candidate genes from intersection analysis.
• Includes results from immune infiltration analysis identifying 12 distinct immune cell types.
• Drug sensitivity analysis covers 112 drugs with differential responses.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is very small (20.5 KB), indicating limited scope, likely containing summary results rather than raw data.

Provenance

Source

figshare, author Qi Zhao.

Collection Method

Integrated analysis of single-cell and whole-genome transcriptomic data.

Time Range

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Freshness

Last updated 2026-04-13 05:21:38; freshness should be verified.

Geography

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