A team led by researchers at the Memorial Sloan-Kettering Cancer Center present Oqtans, an open-source workbench for quantitative transcriptome analysis, that is integrated in the Galaxy framework. Its distinguishing features include customizable computational workflows and a modular pipeline architecture that facilitates comparative assessment of tool and data quality. Oqtans integrates, for the first time, an assortment of sophisticated machine learning-powered tools into Galaxy, that show superior or equal performance to state-of-the-art tools. Implemented tools comprise of a complete transcriptome analysis workflow: short-read alignment, transcript identification/quantification, and differential expression analysis. Moreover, Oqtans is scalable in the cloud in terms of data storage and computing time needs. Finally, Oqtans and Galaxy facilitate persistent storage, data exchange, and documentation of intermediate results and analysis workflows. The researchers illustrate how Oqtans aids the interpretation of data from different experiments in easy to understand use cases. Users can easily create their own workflows and extend Oqtans by integrating specific tools.
Availability – Oqtans is available as (a) a cloud machine image with a demo instance at cloud.oqtans.org, (b) a public Galaxy instance at galaxy.cbio.mskcc.org, (c) a git repository containing all installed software at oqtans.org/git most of which is also avaliable from (d) the Galaxy Toolshed and (e) a share string to use along with Galaxy CloudMan.