Optimizing high performance computing workflow for protein functional annotation

Abstract

Functional annotation of newly sequenced genomes is one of the major challenges in modern biology. With modern sequencing technologies, the protein sequence universe is rapidly expanding. Newly sequenced bacterial genomes alone contain over 7.5 million proteins. The rate of data generation has far surpassed that of protein annotation. The volume of protein data makes manual curation infeasible, whereas a high compute cost limits the utility of existing automated approaches. In this work, we present an improved and optmized automated workflow to enable large-scale protein annotation. The workflow uses high performance computing architectures and a low complexity classification algorithm to assign proteins into existing clusters of orthologous groups of proteins. On the basis of the Position-Specific Iterative Basic Local Alignment Search Tool the algorithm ensures at least 80% specificity and sensitivity of the resulting classifications. The workflow utilizes highly scalable parallel applications for classification and sequence alignment. Using Extreme Science and Engineering Discovery Environment supercomputers, the workflow processed 1,200,000 newly sequenced bacterial proteins. With the rapid expansion of the protein sequence universe, the proposed workflow will enable scientists to annotate big genome data.

XSEDE13 Special Issue Conference Publications

“…The paper on functional annotation of newly sequenced genomes describes an optimized workflow to enable large‐scale protein annotation. It utilizes a special classification algorithm and high performance computing (HPC), and the demonstrated results show capabilities which scientists will be able to utilize to annotate big genome data.…”

Protein Sequence Annotation Tool (PSAT): a centralized web-based meta-server for high-throughput sequence annotations

“…The large volume of sequencing data that are now available has created profound challenges in data transfer and analysis [ 3 ]. High throughput computing on supercomputers was recently introduced to meet these challenges [ 4 , 5 ]. However, high performance computing can be costly, and access to a supercomputing facility can be limited for small laboratories.…”