Table 1_Single-cell genomic profiling of antimicrobial resistance in Escherichia coli from

Runa Furuya's dataset contains single-cell genomic profiling data for Escherichia coli strains from the Densu River in Ghana, focusing on antimicrobial resistance (AMR) and virulence factors. The data was generated using a single-cell amplified genome in gel method after antimicrobial selection, with analysis revealing heterogeneity among strains. The dataset, last updated in April 2026, is a 80.5 KB DOCX file.

Use Cases

• Analyzing AMR gene profiles and virulence factors in environmental E. coli strains based on the single-cell genomic analysis described.
• Conducting pan-genome analysis to compare core and accessory gene clusters based on the predicted 4,814 gene clusters.
• Building phylogenetic trees to assess strain heterogeneity based on the single-cell amplified genomes (SAGs) mentioned.
• Investigating the functional differences between bacterial strains based on the cluster of orthologous gene (COG) analysis results.

Strengths

• Dataset is derived from a novel application of single-cell genomics to an aquatic environment in Ghana, as stated in the conclusion.
• Analysis includes a specific count of 4,814 predicted gene clusters, with 2,264 accessory and 605 singleton clusters.
• Data is licensed under CC-BY-4.0, permitting open sharing and adaptation.

Limitations

• The dataset is very small at 80.5 KB, indicating limited scope or summary-level data.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for statistical modeling.

Provenance

Source

Runa Furuya via figshare.

Collection Method

Single-cell genomic analysis of river water samples after antimicrobial selection, using the single-cell amplified genome in gel method.

Freshness

Last updated 2026-04-23 05:35:01; freshness should be verified.

Geography

Densu River, Ghana.