4DNvestigator: Time Series Genome Structure and Expression Data

A network-based toolbox for analyzing time series genome-wide Hi-C and RNA-seq data, developed by Stephen Lindsly at the University of Michigan. The toolbox provides methods to quantify network entropy, tensor entropy, and statistically significant changes in time series Hi-C data at different genomic scales. The data focuses on the 4D Nucleome, capturing genome organization and output over time.

Use Cases

• Quantify network entropy in time series Hi-C data based on the described analysis methods.
• Identify statistically significant changes in genome structure over time based on the described Hi-C data analysis.
• Integrate time series gene expression (RNA-seq) and genome structure (Hi-C) data for multi-modal analysis based on the toolbox's purpose.
• Analyze the 4D Nucleome (4DN) to study genome organization dynamics based on the dataset's focus.

Strengths

• Toolbox provides specific methods for network entropy and tensor entropy quantification.
• Focuses on the integration of two data types: Hi-C for genome structure and RNA-seq for gene expression.
• Developed at an academic institution (University of Michigan).

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Last update date is unknown; freshness unverified.

Provenance

Source

University of Michigan

Collection Method

Likely generated from genomic sequencing experiments (Hi-C, RNA-seq).