Simultaneous In-Depth Single-Cell Proteomic and Metabolomic Analysis

A multiomics dataset from a study proposing a unified strategy for deep single-cell proteome and metabolome analysis. The data was generated using a hybrid mass spectrometry workflow, achieving an average identification of 3510 protein groups and 255 metabolites per single HepG2 cell. The dataset includes time-resolved profiles of HepG2 cells undergoing sorafenib drug intervention, created by Jie Wu and last updated in April 2026.

Use Cases

• Training models to predict drug response characteristics based on simultaneous proteomic and metabolomic profiles mentioned in the description
• Developing methods for integrating proteomic and metabolomic data from the same single cell as described in the hybrid-scPMA workflow
• Analyzing cellular heterogeneity in cancer cell lines based on the deep protein and metabolite identification achieved
• Benchmarking single-cell multiomics analysis workflows against the reported identification depth of 3510 protein groups and 255 metabolites

Strengths

• Achieves deep dual-omics coverage with an average of 3510 protein groups and 255 metabolites identified per single cell
• Provides time-resolved data on cellular response to a specific drug intervention (sorafenib)
• Data is structured in a tabular XLSX format (427.7 KB), facilitating direct analysis

Limitations

• Row count is unknown, which may limit suitability assessment for large-scale modeling
• Column-level documentation is absent; field semantics must be inferred after download
• The dataset is small in size (427.7 KB), indicating a limited scope or sample count

Provenance

Source

figshare

Collection Method

Generated via an automated single-cell capture workflow integrated with liquid chromatography–mass spectrometry (LC-MS) using a hybrid DIA-DDA detection mode.

Time Range

Time-resolved profiling during drug intervention, but specific dates are not provided.

Freshness

Last updated 2026-04-27 16:04:34; freshness should be verified

Geography

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