Kepler for ‘Omics Bioinformatics

Abstract

There has been a massive increase in the number of large scale biological datasets during the past twenty years, producing new challenges and complexities for analysis. Many of these new datasets are in the ‘omics fields, involving analysis of the genome, transcriptome, and proteome among others. Here, we review ‘omics community-specific factors affecting use of bioinformatics workflow systems. We identify the characteristics of the audience for scientific workflow systems in this community, the existence of a large amount of prewritten software, the use of large amounts of data in a typical analysis, and the growing complexity of analyses as important factors in considering workflow design criteria in this field and also future development of Kepler. Generally, many factors favor much increased use of Kepler in bioinformatics in the future, in particular its advantages in comprehensibility, extensibility, and modifiability of bioinformatics pipelines. We suggest concrete steps to enable further use of this flexible workflow system in ‘omics analyses.