DKOsim: Simulated Double CRISPR Knockout Data for Genetic Interaction Analysis

A synthetic dataset generated by the DKOsim simulation tool to resemble real double knockout CRISPR screens. The dataset includes simulated Log Fold Change (LFC) values, genetic interaction distributions, and replicate correlations. It was created by Yue Gu and last updated on 2026-04 17.

Use Cases

• Benchmarking computational methods for genetic interaction detection based on simulated Log Fold Change (LFC) values.
• Investigating optimal CRISPR library designs based on simulated parameters like depth of coverage and guide efficiency.
• Studying the distribution of synthetic gene-gene interactions between all possible combinations of input genes.

Strengths

• Data is simulated with known ground-truth interactions, addressing the lack of a gold standard dataset mentioned in the description.
• Dataset is small (24.1 KB), facilitating quick download and initial analysis.
• Published under a permissive CC-BY-4.0 license, allowing for reuse and modification.

Limitations

• Row count and column-level documentation are unknown, which may limit suitability assessment.
• Data is entirely synthetic; its applicability to real-world biological systems requires validation.

Provenance

Source

Yue Gu via figshare.

Collection Method

Generated using the Double-CRISPR Knockout Simulation (DKOsim) tool, which employs Monte-Carlo randomization methods.

Time Range

Simulation-based; no real-world temporal coverage.

Freshness

Last updated 2026-04-17 17:51:13; freshness should be verified.

Geography

Simulation-based; no real-world spatial coverage.