MetTailor: dynamic block summary and intensity normalization for robust analysis of mass spectrometry data in metabolomics. (27th July 2015)

• Record Type: Journal Article
• Authors: Chen, Gengbo; Cui, Liang; Teo, Guo Shou; Ong, Choon Nam; Tan, Chuen Seng; Choi, Hyungwon
• Is Part Of: Bioinformatics. Volume 31:Number 22(2015)
• Page Start: 3645
• Page End: 3652
• Publication Date: 2015-07-27
• Subjects: Bioinformatics -- Periodicals; Genomics -- Data processing -- Periodicals; Computational biology -- Periodicals; 572.80285
• DOI: 10.1093/bioinformatics/btv434
• Languages: English
• ISSNs: 1367-4803

Abstract

Abstract : Motivation: Accurate cross-sample peak alignment and reliable intensity normalization is a critical step for robust quantitative analysis in untargetted metabolomics since tandem mass spectrometry (MS/MS) is rarely used for compound identification. Therefore shortcomings in the data processing steps can easily introduce false positives due to misalignments and erroneous normalization adjustments in large sample studies. Results: In this work, we developed a software package MetTailor featuring two novel data preprocessing steps to remedy drawbacks in the existing processing tools. First, we propose a novel dynamic block summarization (DBS) method for correcting misalignments from peak alignment algorithms, which alleviates missing data problem due to misalignments. For the purpose of verifying correct re-alignments, we propose to use the cross-sample consistency in isotopic intensity ratios as a quality metric. Second, we developed a flexible intensity normalization procedure that adjusts normalizing factors against the temporal variations in total ion chromatogram (TIC) along the chromatographic retention time (RT). We first evaluated the DBS algorithm using a curated metabolomics dataset, illustrating that the algorithm identifies misaligned peaks and correctly realigns them with good sensitivity. We next demonstrated the DBS algorithm and the RT-based normalization procedure in a large-scale dataset featuring >100 sera samples in primary Dengue infection study. Although the initial alignment was successful for the majority of peaks, the DBS algorithm still corrected ∼7000 misaligned peaks in this data and many recovered peaks showed consistent isotopic patterns with the peaks they were realigned to. In addition, the RT-based normalization algorithm efficiently removed visible local variations in TIC along the RT, without sacrificing the sensitivity of detecting differentially expressed metabolites. Availability and implementation: The R package MetTailor is freely available at the SourceForge website http://mettailor.sourceforge.net/ . Contact: [e-mail] Supplementary information: Supplementary data are available at Bioinformatics online.