TidyGEO: preparing analysis-ready datasets from Gene Expression Omnibus

Abstract

TidyGEO is a Web-based tool for downloading, tidying, and reformatting data series from Gene Expression Omnibus (GEO). As a freely accessible repository with data from over 6 million biological samples across more than 4000 organisms, GEO provides diverse opportunities for secondary research. Although scientists may find assay data relevant to a given research question, most analyses require sample-level annotations. In GEO, such annotations are stored alongside assay data in delimited, text-based files. However, the structure and semantics of the annotations vary widely from one series to another, and many annotations are not useful for analysis purposes. Thus, every GEO series must be tidied before it is analyzed. Manual approaches may be used, but these are error prone and take time away from other research tasks. Custom computer scripts can be written, but many scientists lack the computational expertise to create such scripts. To address these challenges, we created TidyGEO, which supports essential data-cleaning tasks for sample-level annotations, such as selecting informative columns, renaming columns, splitting or merging columns, standardizing data values, and filtering samples. Additionally, users can integrate annotations with assay data, restructure assay data, and generate code that enables others to reproduce these steps.

RummaGEO: Automatic Mining of Human and Mouse Gene Sets from GEO

“…BioJupies 16 enables users to select samples from GEO studies that were uniformly aligned by ARCHS4 to label control and perturbation conditions, compute differential expression, and perform a variety of analyses and visualizations using automatically executed Jupyter Notebooks in the cloud. In a similar vein, TidyGEO 17 and iLINCS 18 allow users to select GEO series, examine and label their metadata, as well as perform multiple data cleaning and filtering tasks followed by standard downstream analyses such as differential expression and pathway analysis. These bioinformatics web apps, while useful, still require users to manually search and select their studies and conditions.…”