Comparison of pre-processing methods for multiplex bead-based immunoassays

Background High throughput protein expression studies can be performed using bead-based protein immunoassays, such as the Luminex® xMAP® technology. Technical variability is inherent to these experiments and may lead to systematic bias and reduced power. To reduce technical variability, data pre-pro...
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Autor*in:	Rausch, Tanja K. [verfasserIn] Schillert, Arne Ziegler, Andreas Lüking, Angelika Zucht, Hans-Dieter Schulz-Knappe, Peter

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2016

Schlagwörter:	Autoantibody Bead-based Immunoassay Luminex Multiplex Omics Pre-processing Protein

Anmerkung:	© The Author(s). 2016

Übergeordnetes Werk:	Enthalten in: BMC genomics - London : BioMed Central, 2000, 17(2016), 1 vom: 11. Aug.
Übergeordnetes Werk:	volume:17 ; year:2016 ; number:1 ; day:11 ; month:08

Links:	Volltext

DOI / URN:	10.1186/s12864-016-2888-7

Katalog-ID:	SPR027121992

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520			\|a Background High throughput protein expression studies can be performed using bead-based protein immunoassays, such as the Luminex® xMAP® technology. Technical variability is inherent to these experiments and may lead to systematic bias and reduced power. To reduce technical variability, data pre-processing is performed. However, no recommendations exist for the pre-processing of Luminex® xMAP® data. Results We compared 37 different data pre-processing combinations of transformation and normalization methods in 42 samples on 384 analytes obtained from a multiplex immunoassay based on the Luminex® xMAP® technology. We evaluated the performance of each pre-processing approach with 6 different performance criteria. Three performance criteria were plots. All plots were evaluated by 15 independent and blinded readers. Four different combinations of transformation and normalization methods performed well as pre-processing procedure for this bead-based protein immunoassay. Conclusions The following combinations of transformation and normalization were suitable for pre-processing Luminex® xMAP® data in this study: weighted Box-Cox followed by quantile or robust spline normalization (rsn), asinh transformation followed by loess normalization and Box-Cox followed by rsn.
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912			\|a GBV_ILN_2113
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912			\|a GBV_ILN_4307
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912			\|a GBV_ILN_4322
912			\|a GBV_ILN_4323
912			\|a GBV_ILN_4324
912			\|a GBV_ILN_4325
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author_variant	t k r tk tkr a s as a z az a l al h d z hdz p s k psk
matchkey_str	article:14712164:2016----::oprsnfrpoesnmtosomlilxed
hierarchy_sort_str	2016
publishDate	2016
allfields	10.1186/s12864-016-2888-7 doi (DE-627)SPR027121992 (SPR)s12864-016-2888-7-e DE-627 ger DE-627 rakwb eng Rausch, Tanja K. verfasserin aut Comparison of pre-processing methods for multiplex bead-based immunoassays 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2016 Background High throughput protein expression studies can be performed using bead-based protein immunoassays, such as the Luminex® xMAP® technology. Technical variability is inherent to these experiments and may lead to systematic bias and reduced power. To reduce technical variability, data pre-processing is performed. However, no recommendations exist for the pre-processing of Luminex® xMAP® data. Results We compared 37 different data pre-processing combinations of transformation and normalization methods in 42 samples on 384 analytes obtained from a multiplex immunoassay based on the Luminex® xMAP® technology. We evaluated the performance of each pre-processing approach with 6 different performance criteria. Three performance criteria were plots. All plots were evaluated by 15 independent and blinded readers. Four different combinations of transformation and normalization methods performed well as pre-processing procedure for this bead-based protein immunoassay. Conclusions The following combinations of transformation and normalization were suitable for pre-processing Luminex® xMAP® data in this study: weighted Box-Cox followed by quantile or robust spline normalization (rsn), asinh transformation followed by loess normalization and Box-Cox followed by rsn. Autoantibody (dpeaa)DE-He213 Bead-based (dpeaa)DE-He213 Immunoassay (dpeaa)DE-He213 Luminex (dpeaa)DE-He213 Multiplex (dpeaa)DE-He213 Omics (dpeaa)DE-He213 Pre-processing (dpeaa)DE-He213 Protein (dpeaa)DE-He213 Schillert, Arne aut Ziegler, Andreas aut Lüking, Angelika aut Zucht, Hans-Dieter aut Schulz-Knappe, Peter aut Enthalten in BMC genomics London : BioMed Central, 2000 17(2016), 1 vom: 11. Aug. (DE-627)326644954 (DE-600)2041499-7 1471-2164 nnns volume:17 year:2016 number:1 day:11 month:08 https://dx.doi.org/10.1186/s12864-016-2888-7 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 17 2016 1 11 08
spelling	10.1186/s12864-016-2888-7 doi (DE-627)SPR027121992 (SPR)s12864-016-2888-7-e DE-627 ger DE-627 rakwb eng Rausch, Tanja K. verfasserin aut Comparison of pre-processing methods for multiplex bead-based immunoassays 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2016 Background High throughput protein expression studies can be performed using bead-based protein immunoassays, such as the Luminex® xMAP® technology. Technical variability is inherent to these experiments and may lead to systematic bias and reduced power. To reduce technical variability, data pre-processing is performed. However, no recommendations exist for the pre-processing of Luminex® xMAP® data. Results We compared 37 different data pre-processing combinations of transformation and normalization methods in 42 samples on 384 analytes obtained from a multiplex immunoassay based on the Luminex® xMAP® technology. We evaluated the performance of each pre-processing approach with 6 different performance criteria. Three performance criteria were plots. All plots were evaluated by 15 independent and blinded readers. Four different combinations of transformation and normalization methods performed well as pre-processing procedure for this bead-based protein immunoassay. Conclusions The following combinations of transformation and normalization were suitable for pre-processing Luminex® xMAP® data in this study: weighted Box-Cox followed by quantile or robust spline normalization (rsn), asinh transformation followed by loess normalization and Box-Cox followed by rsn. Autoantibody (dpeaa)DE-He213 Bead-based (dpeaa)DE-He213 Immunoassay (dpeaa)DE-He213 Luminex (dpeaa)DE-He213 Multiplex (dpeaa)DE-He213 Omics (dpeaa)DE-He213 Pre-processing (dpeaa)DE-He213 Protein (dpeaa)DE-He213 Schillert, Arne aut Ziegler, Andreas aut Lüking, Angelika aut Zucht, Hans-Dieter aut Schulz-Knappe, Peter aut Enthalten in BMC genomics London : BioMed Central, 2000 17(2016), 1 vom: 11. Aug. (DE-627)326644954 (DE-600)2041499-7 1471-2164 nnns volume:17 year:2016 number:1 day:11 month:08 https://dx.doi.org/10.1186/s12864-016-2888-7 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 17 2016 1 11 08
allfields_unstemmed	10.1186/s12864-016-2888-7 doi (DE-627)SPR027121992 (SPR)s12864-016-2888-7-e DE-627 ger DE-627 rakwb eng Rausch, Tanja K. verfasserin aut Comparison of pre-processing methods for multiplex bead-based immunoassays 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2016 Background High throughput protein expression studies can be performed using bead-based protein immunoassays, such as the Luminex® xMAP® technology. Technical variability is inherent to these experiments and may lead to systematic bias and reduced power. To reduce technical variability, data pre-processing is performed. However, no recommendations exist for the pre-processing of Luminex® xMAP® data. Results We compared 37 different data pre-processing combinations of transformation and normalization methods in 42 samples on 384 analytes obtained from a multiplex immunoassay based on the Luminex® xMAP® technology. We evaluated the performance of each pre-processing approach with 6 different performance criteria. Three performance criteria were plots. All plots were evaluated by 15 independent and blinded readers. Four different combinations of transformation and normalization methods performed well as pre-processing procedure for this bead-based protein immunoassay. Conclusions The following combinations of transformation and normalization were suitable for pre-processing Luminex® xMAP® data in this study: weighted Box-Cox followed by quantile or robust spline normalization (rsn), asinh transformation followed by loess normalization and Box-Cox followed by rsn. Autoantibody (dpeaa)DE-He213 Bead-based (dpeaa)DE-He213 Immunoassay (dpeaa)DE-He213 Luminex (dpeaa)DE-He213 Multiplex (dpeaa)DE-He213 Omics (dpeaa)DE-He213 Pre-processing (dpeaa)DE-He213 Protein (dpeaa)DE-He213 Schillert, Arne aut Ziegler, Andreas aut Lüking, Angelika aut Zucht, Hans-Dieter aut Schulz-Knappe, Peter aut Enthalten in BMC genomics London : BioMed Central, 2000 17(2016), 1 vom: 11. Aug. (DE-627)326644954 (DE-600)2041499-7 1471-2164 nnns volume:17 year:2016 number:1 day:11 month:08 https://dx.doi.org/10.1186/s12864-016-2888-7 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 17 2016 1 11 08
allfieldsGer	10.1186/s12864-016-2888-7 doi (DE-627)SPR027121992 (SPR)s12864-016-2888-7-e DE-627 ger DE-627 rakwb eng Rausch, Tanja K. verfasserin aut Comparison of pre-processing methods for multiplex bead-based immunoassays 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2016 Background High throughput protein expression studies can be performed using bead-based protein immunoassays, such as the Luminex® xMAP® technology. Technical variability is inherent to these experiments and may lead to systematic bias and reduced power. To reduce technical variability, data pre-processing is performed. However, no recommendations exist for the pre-processing of Luminex® xMAP® data. Results We compared 37 different data pre-processing combinations of transformation and normalization methods in 42 samples on 384 analytes obtained from a multiplex immunoassay based on the Luminex® xMAP® technology. We evaluated the performance of each pre-processing approach with 6 different performance criteria. Three performance criteria were plots. All plots were evaluated by 15 independent and blinded readers. Four different combinations of transformation and normalization methods performed well as pre-processing procedure for this bead-based protein immunoassay. Conclusions The following combinations of transformation and normalization were suitable for pre-processing Luminex® xMAP® data in this study: weighted Box-Cox followed by quantile or robust spline normalization (rsn), asinh transformation followed by loess normalization and Box-Cox followed by rsn. Autoantibody (dpeaa)DE-He213 Bead-based (dpeaa)DE-He213 Immunoassay (dpeaa)DE-He213 Luminex (dpeaa)DE-He213 Multiplex (dpeaa)DE-He213 Omics (dpeaa)DE-He213 Pre-processing (dpeaa)DE-He213 Protein (dpeaa)DE-He213 Schillert, Arne aut Ziegler, Andreas aut Lüking, Angelika aut Zucht, Hans-Dieter aut Schulz-Knappe, Peter aut Enthalten in BMC genomics London : BioMed Central, 2000 17(2016), 1 vom: 11. Aug. (DE-627)326644954 (DE-600)2041499-7 1471-2164 nnns volume:17 year:2016 number:1 day:11 month:08 https://dx.doi.org/10.1186/s12864-016-2888-7 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 17 2016 1 11 08
allfieldsSound	10.1186/s12864-016-2888-7 doi (DE-627)SPR027121992 (SPR)s12864-016-2888-7-e DE-627 ger DE-627 rakwb eng Rausch, Tanja K. verfasserin aut Comparison of pre-processing methods for multiplex bead-based immunoassays 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2016 Background High throughput protein expression studies can be performed using bead-based protein immunoassays, such as the Luminex® xMAP® technology. Technical variability is inherent to these experiments and may lead to systematic bias and reduced power. To reduce technical variability, data pre-processing is performed. However, no recommendations exist for the pre-processing of Luminex® xMAP® data. Results We compared 37 different data pre-processing combinations of transformation and normalization methods in 42 samples on 384 analytes obtained from a multiplex immunoassay based on the Luminex® xMAP® technology. We evaluated the performance of each pre-processing approach with 6 different performance criteria. Three performance criteria were plots. All plots were evaluated by 15 independent and blinded readers. Four different combinations of transformation and normalization methods performed well as pre-processing procedure for this bead-based protein immunoassay. Conclusions The following combinations of transformation and normalization were suitable for pre-processing Luminex® xMAP® data in this study: weighted Box-Cox followed by quantile or robust spline normalization (rsn), asinh transformation followed by loess normalization and Box-Cox followed by rsn. Autoantibody (dpeaa)DE-He213 Bead-based (dpeaa)DE-He213 Immunoassay (dpeaa)DE-He213 Luminex (dpeaa)DE-He213 Multiplex (dpeaa)DE-He213 Omics (dpeaa)DE-He213 Pre-processing (dpeaa)DE-He213 Protein (dpeaa)DE-He213 Schillert, Arne aut Ziegler, Andreas aut Lüking, Angelika aut Zucht, Hans-Dieter aut Schulz-Knappe, Peter aut Enthalten in BMC genomics London : BioMed Central, 2000 17(2016), 1 vom: 11. Aug. (DE-627)326644954 (DE-600)2041499-7 1471-2164 nnns volume:17 year:2016 number:1 day:11 month:08 https://dx.doi.org/10.1186/s12864-016-2888-7 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 17 2016 1 11 08
language	English
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author	Rausch, Tanja K.
spellingShingle	Rausch, Tanja K. misc Autoantibody misc Bead-based misc Immunoassay misc Luminex misc Multiplex misc Omics misc Pre-processing misc Protein Comparison of pre-processing methods for multiplex bead-based immunoassays
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topic_title	Comparison of pre-processing methods for multiplex bead-based immunoassays Autoantibody (dpeaa)DE-He213 Bead-based (dpeaa)DE-He213 Immunoassay (dpeaa)DE-He213 Luminex (dpeaa)DE-He213 Multiplex (dpeaa)DE-He213 Omics (dpeaa)DE-He213 Pre-processing (dpeaa)DE-He213 Protein (dpeaa)DE-He213
topic	misc Autoantibody misc Bead-based misc Immunoassay misc Luminex misc Multiplex misc Omics misc Pre-processing misc Protein
topic_unstemmed	misc Autoantibody misc Bead-based misc Immunoassay misc Luminex misc Multiplex misc Omics misc Pre-processing misc Protein
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title	Comparison of pre-processing methods for multiplex bead-based immunoassays
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title_full	Comparison of pre-processing methods for multiplex bead-based immunoassays
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title_sort	comparison of pre-processing methods for multiplex bead-based immunoassays
title_auth	Comparison of pre-processing methods for multiplex bead-based immunoassays
abstract	Background High throughput protein expression studies can be performed using bead-based protein immunoassays, such as the Luminex® xMAP® technology. Technical variability is inherent to these experiments and may lead to systematic bias and reduced power. To reduce technical variability, data pre-processing is performed. However, no recommendations exist for the pre-processing of Luminex® xMAP® data. Results We compared 37 different data pre-processing combinations of transformation and normalization methods in 42 samples on 384 analytes obtained from a multiplex immunoassay based on the Luminex® xMAP® technology. We evaluated the performance of each pre-processing approach with 6 different performance criteria. Three performance criteria were plots. All plots were evaluated by 15 independent and blinded readers. Four different combinations of transformation and normalization methods performed well as pre-processing procedure for this bead-based protein immunoassay. Conclusions The following combinations of transformation and normalization were suitable for pre-processing Luminex® xMAP® data in this study: weighted Box-Cox followed by quantile or robust spline normalization (rsn), asinh transformation followed by loess normalization and Box-Cox followed by rsn. © The Author(s). 2016
abstractGer	Background High throughput protein expression studies can be performed using bead-based protein immunoassays, such as the Luminex® xMAP® technology. Technical variability is inherent to these experiments and may lead to systematic bias and reduced power. To reduce technical variability, data pre-processing is performed. However, no recommendations exist for the pre-processing of Luminex® xMAP® data. Results We compared 37 different data pre-processing combinations of transformation and normalization methods in 42 samples on 384 analytes obtained from a multiplex immunoassay based on the Luminex® xMAP® technology. We evaluated the performance of each pre-processing approach with 6 different performance criteria. Three performance criteria were plots. All plots were evaluated by 15 independent and blinded readers. Four different combinations of transformation and normalization methods performed well as pre-processing procedure for this bead-based protein immunoassay. Conclusions The following combinations of transformation and normalization were suitable for pre-processing Luminex® xMAP® data in this study: weighted Box-Cox followed by quantile or robust spline normalization (rsn), asinh transformation followed by loess normalization and Box-Cox followed by rsn. © The Author(s). 2016
abstract_unstemmed	Background High throughput protein expression studies can be performed using bead-based protein immunoassays, such as the Luminex® xMAP® technology. Technical variability is inherent to these experiments and may lead to systematic bias and reduced power. To reduce technical variability, data pre-processing is performed. However, no recommendations exist for the pre-processing of Luminex® xMAP® data. Results We compared 37 different data pre-processing combinations of transformation and normalization methods in 42 samples on 384 analytes obtained from a multiplex immunoassay based on the Luminex® xMAP® technology. We evaluated the performance of each pre-processing approach with 6 different performance criteria. Three performance criteria were plots. All plots were evaluated by 15 independent and blinded readers. Four different combinations of transformation and normalization methods performed well as pre-processing procedure for this bead-based protein immunoassay. Conclusions The following combinations of transformation and normalization were suitable for pre-processing Luminex® xMAP® data in this study: weighted Box-Cox followed by quantile or robust spline normalization (rsn), asinh transformation followed by loess normalization and Box-Cox followed by rsn. © The Author(s). 2016
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title_short	Comparison of pre-processing methods for multiplex bead-based immunoassays
url	https://dx.doi.org/10.1186/s12864-016-2888-7
remote_bool	true
author2	Schillert, Arne Ziegler, Andreas Lüking, Angelika Zucht, Hans-Dieter Schulz-Knappe, Peter
author2Str	Schillert, Arne Ziegler, Andreas Lüking, Angelika Zucht, Hans-Dieter Schulz-Knappe, Peter
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doi_str	10.1186/s12864-016-2888-7
up_date	2024-07-04T00:28:32.522Z
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Technical variability is inherent to these experiments and may lead to systematic bias and reduced power. To reduce technical variability, data pre-processing is performed. However, no recommendations exist for the pre-processing of Luminex® xMAP® data. Results We compared 37 different data pre-processing combinations of transformation and normalization methods in 42 samples on 384 analytes obtained from a multiplex immunoassay based on the Luminex® xMAP® technology. We evaluated the performance of each pre-processing approach with 6 different performance criteria. Three performance criteria were plots. All plots were evaluated by 15 independent and blinded readers. Four different combinations of transformation and normalization methods performed well as pre-processing procedure for this bead-based protein immunoassay. 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Comparison of pre-processing methods for multiplex bead-based immunoassays

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