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...
Main Authors: | , , , , |
---|---|
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 |