An accelerated background subtraction algorithm for processing high-resolution MS data and its application to metabolite identification
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Updated: Mar 17, 2026

A Strategy for Sensitive, Large Scale Quantitative Metabolomics
Published on: May 27, 2014
Venkateswaran Shekar1, Abhi Shah1, Mohammad Shadid1
1Department of Drug Metabolism & Pharmacokinetics, Takeda Pharmaceuticals International Co., 35 Landsdowne Street, Cambridge, MA, USA.
Background:
Metabolite identification without radiolabeled compound is often challenging because of interference of matrix-related components.
Results:
A novel and an effective background subtraction algorithm (A-BgS) has been developed to process high-resolution mass spectral data that can selectively remove matrix-related components. The use of a graphics processing unit with a multicore central processing unit enhanced processing speed several 1000-fold compared with a single central processing unit. A-BgS algorithm effectively removes background peaks from the mass spectra of biological matrices as demonstrated by the identification of metabolites of delavirdine and metoclopramide.
Conclusion:
The A-BgS algorithm is fast, user friendly and provides reliable removal of matrix-related ions from biological samples, and thus can be very helpful in detection and identification of in vivo and in vitro metabolites.
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