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Efficient algorithms for highly automated evaluation of liquid chromatography - mass spectrometry data
Mid Sweden University, Faculty of Science, Technology and Media, Department of Natural Sciences, Engineering and Mathematics.
2010 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Liquid chromatography coupled to mass spectrometry (LC‐MS) has due to its superiorresolving capabilities become one of the most common analytical instruments fordetermining the constituents in an unknown sample. Each type of sample requires a specificset‐up of the instrument parameters, a procedure referred to as method development.During the requisite experiments, a huge amount of data is acquired which often need to bescrutinised in several different ways. This thesis elucidates data processing methods forhandling this type of data in an automated fashion.The properties of different commonly used digital filters were compared for LC‐MS datade‐noising, of which one was later selected as an essential data processing step during adeveloped peak detection step. Reconstructed data was further discriminated into clusterswith equal retention times into components by an adopted method. This enabled anunsupervised and accurate comparison and matching routine by which components fromthe same sample could be tracked during different chromatographic conditions.The results show that the characteristics of the noise have an impact on the performanceof the tested digital filters. Peak detection with the proposed method was robust to thetested noise and baseline variations but functioned optimally when the analytical peaks hada frequency band different from the uninformative parts of the signal. The algorithm couldeasily be tuned to handle adjacent peaks with lower resolution. It was possible to assignpeaks into components without typical rotational and intensity ambiguities associated tocommon curve resolution methods, which are an alternative approach. The underlyingfunctions for matching components between different experiments yielded satisfactoryresults. The methods have been tested on various experimental data with a high successrate.

Abstract [sv]

De analysinstrument som används för att ta reda på vad ett prov innehåller(och till vilken mängd) måste vanligtvis ställas in för det specifika fallet, för attfungera optimalt. Det finns ofta en mängd olika variabler att undersöka som harmer eller mindre inverkan på resultatet och när provet är okänt kan man oftast inteförutspå de optimala inställningarna i förtid.En vätskekromatograf med en masspektrometer som detektor är ett sådantinstrument som är utvecklat för att separera och identifiera organiska ämnen lösta ivätska. Med detta mycket potenta system kan man ofta med rätt inställningar delaupp de ingående ämnena i provet var för sig och samtidigt erhålla mått som kanrelateras till dess massa och mängd. Detta system används flitigt av analytiskalaboratorer inom bl.a. läkemedelsindustrin för att undersöka stabilitet och renhethos potentiella läkemedel. För att optimera instrumentet för det okända provetkrävs dock att en hel del försök utförs där inställningarna varieras. Syftet är attmed en mindre mängd designade försök bygga en modell som klarar av att peka åtvilket håll de optimala inställningarna finns. Data som genereras från instrumentetför denna typ av applikation är i matrisform då instrumentet scannar och spararintensiteten av ett intervall av massor varje tidpunkt en mätning sker. Om enanalyt når detektorn vid aktuell tidpunkt återges det som en eller flera överlagdanormalfördelade toppar som ett specifikt mönster på en annars oregelbundenbakgrundssignal. Förutom att alla topparna i det färdiga datasetet helst ska varavälseparerade och ha den rätta formen, så ska tiden analysen pågår vara så kortsom möjlig. Det är ändå inte ovanligt att ett färdigt dataset består av tiotalsmiljoner uppmätta intensiteter och att det kan krävas runt 10 försök med olikabetingelser för att åstadkomma ett godtagbart resultat.Dataseten kan dock till mycket stor del innehålla brus och andra störandesignaler vilket gör de extra krångligt att tolka och utvärdera. Eftersom man ävenofta får att komponenterna byter plats i ett dataset när betingelserna ändras kan enmanuell utvärdering ta mycket lång tid.Syftet med denna avhandling har varit att hitta metoder som kan vara till nyttaför den som snabbt och automatiskt behöver jämföra dataset analyserade medolika kromatografiska betingelser, men med samma prov. Det slutgiltiga målet harfrämst varit att identifiera hur olika komponenter i provet har rört sig mellan deolika dataseten, men de steg som ingår kan även nyttjas till andra applikationer.

Place, publisher, year, edition, pages
Sundsvall: Mittuniversitetet , 2010.
Series
Mid Sweden University doctoral thesis, ISSN 1652-893X ; 98
Keyword [en]
Digital filtering, Liquid chromatography, Mass spectrometry, Method
National Category
Chemical Sciences
Identifiers
URN: urn:nbn:se:miun:diva-12991ISBN: 978-91-86694-03-6 (print)OAI: oai:DiVA.org:miun-12991DiVA: diva2:387684
Public defence
2010-12-03, L111, Mittuniversitetet, Sundsvall, Sundsvall, 10:15
Supervisors
Available from: 2011-01-14 Created: 2011-01-14 Last updated: 2011-01-15Bibliographically approved
List of papers
1. An objective comparison of pre-processing methods for enhancement of liquid chromatography-mass spectrometry data
Open this publication in new window or tab >>An objective comparison of pre-processing methods for enhancement of liquid chromatography-mass spectrometry data
Show others...
2007 (English)In: Journal of Chromatography A, ISSN 0021-9673, E-ISSN 1873-3778, Vol. 1172, no 2, 135-150 p.Article in journal (Refereed) Published
Abstract [en]

Four data pre-processing methods have been applied with different settings to data sets obtained from the analysis of a pharmaceutical drug and its degradation products by liquid chromatography�mass spectrometry (LC�MS). The methods compared were the frequently used component detection algorithm (CODA) and three kinds of digital filters�matched filtration (MF), Gaussian second derivative (GSD) and Savitzky�Golay. The aim was to evaluate the performance and robustness of these methods for extracted ion chromatogram (XIC), total ion chromatogram (TIC) and base peak chromatogram (BPC) in the presence of different types of noise. In accordance with theory, the best improvements in signal-to-noise ratio (S/N) of the XICs were obtained with MF under the ideal case with random white noise. However, when highly coloured noise was present, it was found that no improvements in XIC S/N could be obtained with any of the pre-processing methods studied. GSD and CODA did, however, improve the S/N for both TIC and BPC. GSD and CODA also significantly reduced the background in the spectral domain, thereby facilitating the interpretation of the mass spectra. Another advantage associated with CODA and to some extent also with GSD is their data reduction ability.

Keyword
Filter, Liquid chromatography, Mass spectrometry, Chemometrics, Noise
National Category
Chemical Sciences
Identifiers
urn:nbn:se:miun:diva-4516 (URN)10.1016/j.chroma.2007.09.077 (DOI)000251335300006 ()2-s2.0-35748969574 (Scopus ID)5568 (Local ID)5568 (Archive number)5568 (OAI)
Available from: 2008-09-30 Created: 2008-09-30 Last updated: 2016-09-26Bibliographically approved
2. An automatic peak finding method for LC-MS data using Gaussian second derivative filtering
Open this publication in new window or tab >>An automatic peak finding method for LC-MS data using Gaussian second derivative filtering
2009 (English)In: Journal of Separation Science, ISSN 1615-9306, E-ISSN 1615-9314, Vol. 32, no 22, 3906-3918 p.Article in journal (Refereed) Published
Abstract [en]

A highly automated procedure for localising and characterising peaks in the chromatographic time domain of LC-MS data has been developed. The work was initiated by an identified need to facilitate the detection and tracking of chromatographic peaks during method development for the analysis of impurities in pharmaceutical products. The algorithm is mainly based on a digital filter for which the settings are automatically adapted to the data set under study. The procedure was evaluated for synthetic data sets with various S/N levels, peak widths and baseline properties. It was found that even for the worst case tested with S/N=10 and a high variability in the baseline, 94% of the simulated analytical peaks could be detected without producing any false-positive identifications. Furthermore, the number of correctly estimated peak heights and peak widths falling within a 10% error of the true values were 94 and 91%, respectively. For experimental data sets, peak height, and width estimations were more difficult, but the processed reconstructions showed an excellent agreement with the analytical signals of the raw data, and also a clearly improved visualisation in total ion- and base-peak chromatograms.

Place, publisher, year, edition, pages
Weinheim: Wiley-VCH Verlag, 2009
Keyword
Liquid chromatography, Mass spectrometry, Method development, Noise, Peak detection
National Category
Other Basic Medicine
Identifiers
urn:nbn:se:miun:diva-10799 (URN)10.1002/jssc.200900395 (DOI)000273993500007 ()19882622 (PubMedID)2-s2.0-76649123143 (Scopus ID)
Available from: 2009-12-30 Created: 2009-12-30 Last updated: 2011-01-14Bibliographically approved
3. A component tracking algorithm for accelerated and improved liquid chromatography-mass spectrometry method development
Open this publication in new window or tab >>A component tracking algorithm for accelerated and improved liquid chromatography-mass spectrometry method development
2010 (English)In: Journal of Chromatography A, ISSN 0021-9673, E-ISSN 1873-3778, Vol. 1217, no 52, 8195-8204 p.Article in journal (Refereed) Published
Abstract [en]

A method for tracking of sample components during liquid chromatography–mass spectrometry (LC–MS) method development has been proposed. The method manages to, fully automatically and without user intervention, find the chromatographic peaks in the data sets, discriminate them to sample components and track them when the separation conditions have been changed. The algorithm utilises the resolution obtained from all considered data sets and has the ability to discriminate the non informative parts. The technique has a great sensitivity even in cases where a majority of the tracked components cannot easily be spotted by means of traditional total ion chromatogram (TIC) or base peak chromatogram (BPC) representations. The method was tested on an experimental sample using six different columns and an average of 79% of the suggested sample components could be successfully tracked at a minimum area of 0.05% of the main component in the sample. 66 components with 79–92% of the total suggested component area were able to be tracked between all data sets. The method could be used to rapidly investigate selectivity during different types of separation conditions.

Keyword
Liquid chromatography, mass spectrometry, chemometrics, peak detection, peak tracking
National Category
Analytical Chemistry Analytical Chemistry
Identifiers
urn:nbn:se:miun:diva-12612 (URN)10.1016/j.chroma.2010.10.083 (DOI)000285899400015 ()21081230 (PubMedID)2-s2.0-78649880394 (Scopus ID)
Available from: 2010-12-13 Created: 2010-12-13 Last updated: 2016-09-22Bibliographically approved
4. Combined use of algorithms for peak picking, peak tracking and retention modelling to optimize the chromatographic conditions for liquid chromatography-mass spectrometry analysis of fluocinolone acetonide and its degradation products
Open this publication in new window or tab >>Combined use of algorithms for peak picking, peak tracking and retention modelling to optimize the chromatographic conditions for liquid chromatography-mass spectrometry analysis of fluocinolone acetonide and its degradation products
2011 (English)In: Analytica Chimica Acta, ISSN 0003-2670, E-ISSN 1873-4324, Vol. 704, no 1-2, 180-188 p.Article in journal (Refereed) Published
Abstract [en]

A strategy for rapid optimization of liquid chromatography column temperature and gradient shape is presented. The optimization as such is based on the well established retention and peak width models implemented in software like e.g. DryLab and LC simulator. The novel part of the strategy is a highly automated processing algorithm for detection and tracking of chromatographic peaks in noisy liquid chromatography-mass spectrometry (LC-MS) data. The strategy is presented and visualized by the optimization of the separation of two degradants present in ultraviolet (UV) exposed fluocinolone acetonide. It should be stressed, however, that it can be utilized for LC-MS analysis of any sample and application where several runs are conducted on the same sample. In the application presented, 30 components that were difficult or impossible to detect in the UV data could be automatically detected and tracked in the MS data by using the proposed strategy. The number of correctly tracked components was above 95%. Using the parameters from the reconstructed data sets to the model gave good agreement between predicted and observed retention times at optimal conditions. The area of the smallest tracked component was estimated to 0.08% compared to the main component, a level relevant for the characterization of impurities in the pharmaceutical industry.

Keyword
Liquid chromatography; Mass spectrometry; Method development; Peak tracking
National Category
Natural Sciences
Identifiers
urn:nbn:se:miun:diva-12990 (URN)10.1016/j.aca.2011.07.047 (DOI)000296824600020 ()21907036 (PubMedID)2-s2.0-80052537329 (Scopus ID)
Available from: 2011-01-14 Created: 2011-01-14 Last updated: 2012-08-09Bibliographically approved

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