Liquid chromatography-mass spectrometry (LC-MS) is often used in the analysis of peptides to separate the individual test subjects and yield less complex mass spectra, researchers in the US note.
However, this can create thousands of spectra with erroneous records caused by heavy isotopes and charge characteristics.
The scientists argue that existing algorithms for clarifying the output of LC-MS analysis can cause further problems as they are not designed to deal with overlapping spectra.
Now the team, from Texas A&M University, the University of Texas at San Antonio, the Translational Genomics Research Institution in Arizona and the University of Texas M D Anderson Cancer Center, have published their own algorithm, named BPDA, in BMC Bioinformatics.
BPDA uses a Bayesian approach to clarify the spectra retrieved from the LC-MS process, with minimal mean observed errors between the inferred and observed spectrum in each case.
BMC Bioinformatics is concerned with the latest statistical and computational methods for scientific analysis.
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