IDEOM: an Excel interface for analysis of LC-MS-based metabolomics data

The application of emerging metabolomics technologies to the comprehensive investigation of cellular biochemistry has been limited by bottlenecks in data processing, particularly noise filtering and metabolite identification. IDEOM provides a user-friendly data processing application that automates...

Full description

Saved in:
Bibliographic Details
Published in:Bioinformatics (Oxford, England) England), 2012-04, Vol.28 (7), p.1048-1049
Main Authors: CREEK, Darren J, JANKEVICS, Andris, BURGESS, Karl E. V, BREITLING, Rainer, BARRETT, Michael P
Format: Article
Language:English
Subjects:
Biological and medical sciences
Chromatography, Liquid - methods
Computational Biology - methods
Databases, Factual
Fundamental and applied biological sciences. Psychology
General aspects
Mass Spectrometry - methods
Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects)
Metabolomics
Software
User-Computer Interface
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The application of emerging metabolomics technologies to the comprehensive investigation of cellular biochemistry has been limited by bottlenecks in data processing, particularly noise filtering and metabolite identification. IDEOM provides a user-friendly data processing application that automates filtering and identification of metabolite peaks, paying particular attention to common sources of noise and false identifications generated by liquid chromatography-mass spectrometry (LC-MS) platforms. Building on advanced processing tools such as mzMatch and XCMS, it allows users to run a comprehensive pipeline for data analysis and visualization from a graphical user interface within Microsoft Excel, a familiar program for most biological scientists. IDEOM is provided free of charge at http://mzmatch.sourceforge.net/ideom.html, as a macro-enabled spreadsheet (.xlsb). Implementation requires Microsoft Excel (2007 or later). R is also required for full functionality. michael.barrett@glasgow.ac.uk Supplementary data are available at Bioinformatics online.
ISSN:1367-4803
1367-4811
DOI:10.1093/bioinformatics/bts069