Heat*seq: an interactive web tool for high-throughput sequencing experiment comparison with public data.

Area of Science:

• Genomics
• Bioinformatics
• Computational Biology

Background:

• High-throughput sequencing experiments (e.g., ChIP-seq, RNA-seq) are increasingly accessible to smaller labs.
• Comparing individual lab experiments to vast public domain data is challenging due to bioinformatics expertise limitations.
• Existing tools offer gene-level comparisons but lack a genome-wide perspective.

Purpose of the Study:

• To develop a web-based tool, Heat*seq, for genome-scale comparison of user-submitted high-throughput sequencing data against public domain repositories.
• To provide researchers with a tool for contextualizing their experimental results within a broader genomic landscape.

Main Methods:

• Development of Heat*seq, a web-tool facilitating genome-wide comparisons.
• Integration of diverse high-throughput sequencing data types: chromatin immunoprecipitation followed by sequencing (ChIP-seq), RNA-sequencing (RNA-seq), and Cap Analysis of Gene Expression (CAGE).
• Inclusion of over 12,000 public domain experiments across human, mouse, and Drosophila species.
• Implementation of interactive correlation heatmaps with dynamic data subsetting capabilities.

Main Results:

• Heat*seq enables genome-wide comparison of user experiments with public data.
• The tool provides interactive correlation heatmaps for visualizing relationships between datasets.
• Users can dynamically subset datasets to contextualize their experiments effectively.
• High-quality figures and tables are generated and downloadable in multiple formats.

Conclusions:

• Heat*seq addresses the need for accessible, genome-wide comparison of high-throughput sequencing data.
• The tool empowers researchers, particularly those with limited bioinformatics expertise, to leverage public domain data.
• Heat*seq facilitates deeper insights by enabling contextualization of experimental results within a large-scale genomic framework.