The Einstein Genome Gateway using WASP - a high throughput multi-layered life sciences portal for XSEDE

Area of Science:

• Genomics and Epigenomics
• Bioinformatics and Computational Biology

Background:

• Massively-parallel sequencing (MPS) generates vast and diverse datasets, posing significant challenges for data management, processing, and analysis in human genome research.
• Existing infrastructure struggles to efficiently handle the scale and complexity of genomic and epigenomic data.

Purpose of the Study:

• To introduce the Wiki-based Automated Sequence Processor (WASP) as a solution for managing and processing large-scale genomic datasets.
• To highlight WASP's role as a middleware solution for abstracting computational complexity and enhancing user interactivity with genomic technologies.

Main Methods:

• Development of the Wiki-based Automated Sequence Processor (WASP) at Albert Einstein College of Medicine.
• Integration of sequencing platforms, assays, sample metadata, and automated workflows.
• Deployment on a heterogeneous high-performance computing cluster with a web-based GUI.

Main Results:

• WASP successfully processes 4-6 TB of data weekly, with a cumulative ~1 PB processed.
• The system provides sequenced, quality-controlled, and mapped sequence data.
• WASP has significantly improved user interaction with complex genomic data processing.

Conclusions:

• WASP effectively manages and processes large-scale genomic data, overcoming major research hurdles.
• WASP serves as an ideal middleware solution, simplifying computational complexity for users.
• WASP is foundational for developing grid-enabled resources like the Einstein Genome Gateway for the XSEDE program.