amsrpm: Robust Point Matching for Retention Time Aligment of LC/MS Data with R

Proteomics is the study of the abundance, function and dynamics of all proteins present in a living organism, and mass spectrometry (MS) has become its most important tool due to its unmatched sensitivity, resolution and potential for high-throughput experimentation. A frequently used variant of mas...

Full description

Bibliographic Details
Main Authors: Marc Kirchner, Benjamin Saussen, Hanno Steen, Judith A. J. Steen, Fred A. Hamprecht
Format: Article
Language:English
Published: Foundation for Open Access Statistics 2007-01-01
Series:Journal of Statistical Software
Subjects:
Online Access:http://www.jstatsoft.org/v18/i04/paper
id doaj-63048c9d81004f5fb23827f9620635cb
record_format Article
spelling doaj-63048c9d81004f5fb23827f9620635cb2020-11-24T23:05:44ZengFoundation for Open Access StatisticsJournal of Statistical Software1548-76602007-01-01184amsrpm: Robust Point Matching for Retention Time Aligment of LC/MS Data with RMarc KirchnerBenjamin SaussenHanno SteenJudith A. J. SteenFred A. HamprechtProteomics is the study of the abundance, function and dynamics of all proteins present in a living organism, and mass spectrometry (MS) has become its most important tool due to its unmatched sensitivity, resolution and potential for high-throughput experimentation. A frequently used variant of mass spectrometry is coupled with liquid chromatography (LC) and is denoted as “LC/MS”. It produces two-dimensional raw data, where significant distortions along one of the dimensions can occur between different runs on the same instrument, and between instruments. A compensation of these distortions is required to allow for comparisons between and inference based on different experiments. This article introduces the amsrpm software package. It implements a variant of the Robust Point Matching (RPM) algorithm that is tailored for the alignment of LC and LC/MS experiments. Problem-specific enhancements include a specialized dissimilarity measure, and means to enforce smoothness and monotonicity of the estimated transformation function. The algorithm does not rely on pre-specified landmarks, it is insensitive towards outliers and capable of modeling nonlinear distortions. Its usefulness is demonstrated using both simulated and experimental data. The software is available as an open source package for the statistical programming language R.http://www.jstatsoft.org/v18/i04/paperregistrationalignmentsequence alignmentdynamic time warpingmonotone regressionretention timeelutionLC/MSrobust point matchingchromatogram warping
collection DOAJ
language English
format Article
sources DOAJ
author Marc Kirchner
Benjamin Saussen
Hanno Steen
Judith A. J. Steen
Fred A. Hamprecht
spellingShingle Marc Kirchner
Benjamin Saussen
Hanno Steen
Judith A. J. Steen
Fred A. Hamprecht
amsrpm: Robust Point Matching for Retention Time Aligment of LC/MS Data with R
Journal of Statistical Software
registration
alignment
sequence alignment
dynamic time warping
monotone regression
retention time
elution
LC/MS
robust point matching
chromatogram warping
author_facet Marc Kirchner
Benjamin Saussen
Hanno Steen
Judith A. J. Steen
Fred A. Hamprecht
author_sort Marc Kirchner
title amsrpm: Robust Point Matching for Retention Time Aligment of LC/MS Data with R
title_short amsrpm: Robust Point Matching for Retention Time Aligment of LC/MS Data with R
title_full amsrpm: Robust Point Matching for Retention Time Aligment of LC/MS Data with R
title_fullStr amsrpm: Robust Point Matching for Retention Time Aligment of LC/MS Data with R
title_full_unstemmed amsrpm: Robust Point Matching for Retention Time Aligment of LC/MS Data with R
title_sort amsrpm: robust point matching for retention time aligment of lc/ms data with r
publisher Foundation for Open Access Statistics
series Journal of Statistical Software
issn 1548-7660
publishDate 2007-01-01
description Proteomics is the study of the abundance, function and dynamics of all proteins present in a living organism, and mass spectrometry (MS) has become its most important tool due to its unmatched sensitivity, resolution and potential for high-throughput experimentation. A frequently used variant of mass spectrometry is coupled with liquid chromatography (LC) and is denoted as “LC/MS”. It produces two-dimensional raw data, where significant distortions along one of the dimensions can occur between different runs on the same instrument, and between instruments. A compensation of these distortions is required to allow for comparisons between and inference based on different experiments. This article introduces the amsrpm software package. It implements a variant of the Robust Point Matching (RPM) algorithm that is tailored for the alignment of LC and LC/MS experiments. Problem-specific enhancements include a specialized dissimilarity measure, and means to enforce smoothness and monotonicity of the estimated transformation function. The algorithm does not rely on pre-specified landmarks, it is insensitive towards outliers and capable of modeling nonlinear distortions. Its usefulness is demonstrated using both simulated and experimental data. The software is available as an open source package for the statistical programming language R.
topic registration
alignment
sequence alignment
dynamic time warping
monotone regression
retention time
elution
LC/MS
robust point matching
chromatogram warping
url http://www.jstatsoft.org/v18/i04/paper
work_keys_str_mv AT marckirchner amsrpmrobustpointmatchingforretentiontimealigmentoflcmsdatawithr
AT benjaminsaussen amsrpmrobustpointmatchingforretentiontimealigmentoflcmsdatawithr
AT hannosteen amsrpmrobustpointmatchingforretentiontimealigmentoflcmsdatawithr
AT judithajsteen amsrpmrobustpointmatchingforretentiontimealigmentoflcmsdatawithr
AT fredahamprecht amsrpmrobustpointmatchingforretentiontimealigmentoflcmsdatawithr
_version_ 1725625953819820032