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Abstract
Recently, interest in untargeted metabolomics has become prevalent in the general scientific community among an increasing number of investigators. The majority of these investigators, however, do not have the bioinformatic expertise that has been required to process metabolomic data by using command-line driven software programs. Here we introduce a novel platform to process untargeted metabolomic data that uses an intuitive graphical interface and does not require installation or technical expertise. This platform, called XCMS Online, is a web-based version of the widely used XCMS software that allows users to easily upload and process liquid chromatography/mass spectrometry data with only a few mouse clicks. XCMS Online provides a solution for the complete untargeted metabolomic workflow including feature detection, retention time correction, alignment, annotation, statistical analysis, and data visualization. Results can be browsed online in an interactive, customizable table showing statistics, chromatograms, and putative METLIN identities for each metabolite. Additionally, all results and images can be downloaded as zip files for offline analysis and publication. XCMS Online is available at https://xcmsonline.scripps.edu.
Highlights
Interest in untargeted metabolomics has become prevalent in the general scientific community among an increasing number of investigators
Several analytical technologies can be used to perform untargeted metabolomics, often liquid chromatography/mass spectrometry (LC/MS) is the technique of choice given the large number of metabolites that can be simultaneously measured in a single analysis
Unlike the web-based tools MetaboAnalyst[5] and metaP-Server[6] that have been recently introduced to perform statistical analysis of preprocessed data, XCMS Online is a solution for the entire untargeted metabolomic workflow ranging from the computationally expensive raw data processing and retention time correction calculations to statistical analysis and metabolite assignment
Summary
Interest in untargeted metabolomics has become prevalent in the general scientific community among an increasing number of investigators. These non-linear deviations can complicate interpretation of even a subset of untargeted metabolomic data and reinforce the need of bioinformatic software that performs automated data processing, such as retention time alignment. In response to the growing interest from the general scientific community for a user-friendly program to process untargeted metabolomic data, we have created a web-based platform called XCMS Online.
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