Grant Number:	3U01CA235488-02S1 Interpret this number
Primary Investigator:	Kechris-Mays, Katherina
Organization:	University Of Colorado Denver
Project Title:	Addressing Sparsity in Metabolomics Data Analysis
Fiscal Year:	2019

Comprehensive profiling of the small molecule repertoire in a sample is referred to as metabolomics, and is being used to address a variety of scientific questions in biomedical studies. Recent technological advances in mass spectrometry-based metabolomics have allowed for more comprehensive and sensitive measurements of metabolites. Despite the technological advances, the bottleneck for taking full advantage of metabolomics data is often the availability and usability of analysis tools. The goal of the parent U01 award (U01CA235488) is to develop novel statistical methods and software for the research community to improve the utilization of metabolomics data, which will help maximize the potential of metabolomics to provide new discoveries in disease etiology, diagnosis, and drug development. Software tools specifically designed for metabolomics data, like those proposed in the parent U01 award, are being developed at an increasing rate with hundreds of available tools. Many of these tools are open-source and freely available, but are very diverse with respect to language, data formats, and stages in the metabolomics pipeline. Several of the challenges recognized in the NIH Common Fund Metabolomics Program are to “meet increasing demand for user-friendly, open-source, bioinformatics tools for data analysis and interpretation” and “coordinate community-wide identification and adoption of best practices for rigor, reproducibility and data reuse.” This supplement proposal aims to promote Program goals by surveying and understanding the landscape of available software tools, not only developed by consortium members, but also by the broader metabolomics community. In Aim 1, we will survey publicly available software tools and report the interoperability between tools, which can be used to develop workflows for the different stages of metabolomics data analyses. In Aim 2, since many software tools are no longer maintained, we will identify the subset of packages that can still be installed, in addition to performing code meta-data analysis to identify factors that correlate with activity and impact of software tools. In Aim 3, we will disseminate the software database with the support of the Program, and document the results of our survey including trends associated with the most frequently used software tools. We will work with the Metabolomics Consortium Coordinating Center (M3C), in meta-data definitions, database hosting and promotion of the database. The results of this survey will provide information to support the development of software for the metabolomics community.





None. See parent grant details.