The ISMARA client.

Area of Science:

• Bioinformatics
• Computational Biology
• Genomics

Background:

• High-throughput gene expression and chromatin data analysis is crucial for understanding regulatory networks.
• Large next-generation sequencing (NGS) datasets pose significant challenges due to long upload times and data privacy concerns.
• Existing tools like ISMARA require uploading raw data, creating bottlenecks for users.

Purpose of the Study:

• To develop a solution for efficient local pre-processing of large NGS datasets for ISMARA analysis.
• To reduce data upload times and address concerns regarding the transfer of proprietary raw data.
• To enable automated, streamlined regulatory network inference using ISMARA.

Main Methods:

• Development of a stand-alone client application for local data pre-processing.
• The client application handles RNA-seq and ChIP-seq data.
• Automated uploading of small, processed summary files to the ISMARA server.

Main Results:

• Achieved file size reduction by up to a factor of 1000.
• Reduced data upload times from hours to seconds.
• Enabled fully automated ISMARA analysis with local pre-processing.

Conclusions:

• The new client application significantly improves the efficiency and accessibility of ISMARA for analyzing large NGS datasets.
• Local pre-processing addresses data size and privacy concerns, facilitating wider adoption of ISMARA.
• This advancement streamlines the inference of key regulators and regulatory interactions from genomic data.