Normalization of microarray expression data using within-pedigree pool and its effect on linkage analysis
Abstract "Genetical genomics", the study of natural genetic variation combining data from genetic marker-based studies with gene expression analyses, has exploded with the recent development of advanced microarray technologies. To account for systematic variation known to exist in microarr...
Ausführliche Beschreibung
Autor*in: |
Kim, Yoonhee [verfasserIn] |
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E-Artikel |
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Englisch |
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2007 |
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© Kim et al; licensee BioMed Central Ltd. 2007. This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License ( |
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Übergeordnetes Werk: |
Enthalten in: BMC proceedings - London : BioMed Central, 2007, 1(2007), Suppl 1 vom: 18. Dez. |
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Übergeordnetes Werk: |
volume:1 ; year:2007 ; number:Suppl 1 ; day:18 ; month:12 |
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DOI / URN: |
10.1186/1753-6561-1-S1-S152 |
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SPR028427599 |
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520 | |a Abstract "Genetical genomics", the study of natural genetic variation combining data from genetic marker-based studies with gene expression analyses, has exploded with the recent development of advanced microarray technologies. To account for systematic variation known to exist in microarray data, it is critical to properly normalize gene expression traits before performing genetic linkage analyses. However, imposing equal means and variances across pedigrees can over-correct for the true biological variation by ignoring familial correlations in expression values. We applied the robust multiarray average (RMA) method to gene expression trait data from 14 Centre d'Etude du Polymorphisme Humain (CEPH) Utah pedigrees provided by GAW15 (Genetic Analysis Workshop 15). We compared the RMA normalization method using within-pedigree pools to RMA normalization using all individuals in a single pool, which ignores pedigree membership, and investigated the effects of these different methods on 18 gene expression traits previously found to be linked to regions containing the corresponding structural locus. Familial correlation coefficients of the expressed traits were stronger when traits were normalized within pedigrees. Surprisingly, the linkage plots for these traits were similar, suggesting that although heritability increases when traits are normalized within pedigrees, the strength of linkage evidence does not necessarily change substantially. | ||
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10.1186/1753-6561-1-S1-S152 doi (DE-627)SPR028427599 (SPR)1753-6561-1-S1-S152-e DE-627 ger DE-627 rakwb eng Kim, Yoonhee verfasserin aut Normalization of microarray expression data using within-pedigree pool and its effect on linkage analysis 2007 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Kim et al; licensee BioMed Central Ltd. 2007. This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License ( Abstract "Genetical genomics", the study of natural genetic variation combining data from genetic marker-based studies with gene expression analyses, has exploded with the recent development of advanced microarray technologies. To account for systematic variation known to exist in microarray data, it is critical to properly normalize gene expression traits before performing genetic linkage analyses. However, imposing equal means and variances across pedigrees can over-correct for the true biological variation by ignoring familial correlations in expression values. We applied the robust multiarray average (RMA) method to gene expression trait data from 14 Centre d'Etude du Polymorphisme Humain (CEPH) Utah pedigrees provided by GAW15 (Genetic Analysis Workshop 15). We compared the RMA normalization method using within-pedigree pools to RMA normalization using all individuals in a single pool, which ignores pedigree membership, and investigated the effects of these different methods on 18 gene expression traits previously found to be linked to regions containing the corresponding structural locus. Familial correlation coefficients of the expressed traits were stronger when traits were normalized within pedigrees. Surprisingly, the linkage plots for these traits were similar, suggesting that although heritability increases when traits are normalized within pedigrees, the strength of linkage evidence does not necessarily change substantially. Normalization Method (dpeaa)DE-He213 Genetical Genomic (dpeaa)DE-He213 Normalization Pool (dpeaa)DE-He213 Familial Correlation (dpeaa)DE-He213 Robust Multiarray Average (dpeaa)DE-He213 Doan, Betty Q aut Duggal, Priya aut Bailey-Wilson, Joan E aut Enthalten in BMC proceedings London : BioMed Central, 2007 1(2007), Suppl 1 vom: 18. Dez. (DE-627)559080840 (DE-600)2411867-9 1753-6561 nnns volume:1 year:2007 number:Suppl 1 day:18 month:12 https://dx.doi.org/10.1186/1753-6561-1-S1-S152 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 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_2014 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 1 2007 Suppl 1 18 12 |
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10.1186/1753-6561-1-S1-S152 doi (DE-627)SPR028427599 (SPR)1753-6561-1-S1-S152-e DE-627 ger DE-627 rakwb eng Kim, Yoonhee verfasserin aut Normalization of microarray expression data using within-pedigree pool and its effect on linkage analysis 2007 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Kim et al; licensee BioMed Central Ltd. 2007. This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License ( Abstract "Genetical genomics", the study of natural genetic variation combining data from genetic marker-based studies with gene expression analyses, has exploded with the recent development of advanced microarray technologies. To account for systematic variation known to exist in microarray data, it is critical to properly normalize gene expression traits before performing genetic linkage analyses. However, imposing equal means and variances across pedigrees can over-correct for the true biological variation by ignoring familial correlations in expression values. We applied the robust multiarray average (RMA) method to gene expression trait data from 14 Centre d'Etude du Polymorphisme Humain (CEPH) Utah pedigrees provided by GAW15 (Genetic Analysis Workshop 15). We compared the RMA normalization method using within-pedigree pools to RMA normalization using all individuals in a single pool, which ignores pedigree membership, and investigated the effects of these different methods on 18 gene expression traits previously found to be linked to regions containing the corresponding structural locus. Familial correlation coefficients of the expressed traits were stronger when traits were normalized within pedigrees. Surprisingly, the linkage plots for these traits were similar, suggesting that although heritability increases when traits are normalized within pedigrees, the strength of linkage evidence does not necessarily change substantially. Normalization Method (dpeaa)DE-He213 Genetical Genomic (dpeaa)DE-He213 Normalization Pool (dpeaa)DE-He213 Familial Correlation (dpeaa)DE-He213 Robust Multiarray Average (dpeaa)DE-He213 Doan, Betty Q aut Duggal, Priya aut Bailey-Wilson, Joan E aut Enthalten in BMC proceedings London : BioMed Central, 2007 1(2007), Suppl 1 vom: 18. Dez. (DE-627)559080840 (DE-600)2411867-9 1753-6561 nnns volume:1 year:2007 number:Suppl 1 day:18 month:12 https://dx.doi.org/10.1186/1753-6561-1-S1-S152 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 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_2014 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 1 2007 Suppl 1 18 12 |
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10.1186/1753-6561-1-S1-S152 doi (DE-627)SPR028427599 (SPR)1753-6561-1-S1-S152-e DE-627 ger DE-627 rakwb eng Kim, Yoonhee verfasserin aut Normalization of microarray expression data using within-pedigree pool and its effect on linkage analysis 2007 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Kim et al; licensee BioMed Central Ltd. 2007. This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License ( Abstract "Genetical genomics", the study of natural genetic variation combining data from genetic marker-based studies with gene expression analyses, has exploded with the recent development of advanced microarray technologies. To account for systematic variation known to exist in microarray data, it is critical to properly normalize gene expression traits before performing genetic linkage analyses. However, imposing equal means and variances across pedigrees can over-correct for the true biological variation by ignoring familial correlations in expression values. We applied the robust multiarray average (RMA) method to gene expression trait data from 14 Centre d'Etude du Polymorphisme Humain (CEPH) Utah pedigrees provided by GAW15 (Genetic Analysis Workshop 15). We compared the RMA normalization method using within-pedigree pools to RMA normalization using all individuals in a single pool, which ignores pedigree membership, and investigated the effects of these different methods on 18 gene expression traits previously found to be linked to regions containing the corresponding structural locus. Familial correlation coefficients of the expressed traits were stronger when traits were normalized within pedigrees. Surprisingly, the linkage plots for these traits were similar, suggesting that although heritability increases when traits are normalized within pedigrees, the strength of linkage evidence does not necessarily change substantially. Normalization Method (dpeaa)DE-He213 Genetical Genomic (dpeaa)DE-He213 Normalization Pool (dpeaa)DE-He213 Familial Correlation (dpeaa)DE-He213 Robust Multiarray Average (dpeaa)DE-He213 Doan, Betty Q aut Duggal, Priya aut Bailey-Wilson, Joan E aut Enthalten in BMC proceedings London : BioMed Central, 2007 1(2007), Suppl 1 vom: 18. Dez. (DE-627)559080840 (DE-600)2411867-9 1753-6561 nnns volume:1 year:2007 number:Suppl 1 day:18 month:12 https://dx.doi.org/10.1186/1753-6561-1-S1-S152 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 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_2014 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 1 2007 Suppl 1 18 12 |
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10.1186/1753-6561-1-S1-S152 doi (DE-627)SPR028427599 (SPR)1753-6561-1-S1-S152-e DE-627 ger DE-627 rakwb eng Kim, Yoonhee verfasserin aut Normalization of microarray expression data using within-pedigree pool and its effect on linkage analysis 2007 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Kim et al; licensee BioMed Central Ltd. 2007. This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License ( Abstract "Genetical genomics", the study of natural genetic variation combining data from genetic marker-based studies with gene expression analyses, has exploded with the recent development of advanced microarray technologies. To account for systematic variation known to exist in microarray data, it is critical to properly normalize gene expression traits before performing genetic linkage analyses. However, imposing equal means and variances across pedigrees can over-correct for the true biological variation by ignoring familial correlations in expression values. We applied the robust multiarray average (RMA) method to gene expression trait data from 14 Centre d'Etude du Polymorphisme Humain (CEPH) Utah pedigrees provided by GAW15 (Genetic Analysis Workshop 15). We compared the RMA normalization method using within-pedigree pools to RMA normalization using all individuals in a single pool, which ignores pedigree membership, and investigated the effects of these different methods on 18 gene expression traits previously found to be linked to regions containing the corresponding structural locus. Familial correlation coefficients of the expressed traits were stronger when traits were normalized within pedigrees. Surprisingly, the linkage plots for these traits were similar, suggesting that although heritability increases when traits are normalized within pedigrees, the strength of linkage evidence does not necessarily change substantially. Normalization Method (dpeaa)DE-He213 Genetical Genomic (dpeaa)DE-He213 Normalization Pool (dpeaa)DE-He213 Familial Correlation (dpeaa)DE-He213 Robust Multiarray Average (dpeaa)DE-He213 Doan, Betty Q aut Duggal, Priya aut Bailey-Wilson, Joan E aut Enthalten in BMC proceedings London : BioMed Central, 2007 1(2007), Suppl 1 vom: 18. Dez. (DE-627)559080840 (DE-600)2411867-9 1753-6561 nnns volume:1 year:2007 number:Suppl 1 day:18 month:12 https://dx.doi.org/10.1186/1753-6561-1-S1-S152 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 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_2014 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 1 2007 Suppl 1 18 12 |
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10.1186/1753-6561-1-S1-S152 doi (DE-627)SPR028427599 (SPR)1753-6561-1-S1-S152-e DE-627 ger DE-627 rakwb eng Kim, Yoonhee verfasserin aut Normalization of microarray expression data using within-pedigree pool and its effect on linkage analysis 2007 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Kim et al; licensee BioMed Central Ltd. 2007. This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License ( Abstract "Genetical genomics", the study of natural genetic variation combining data from genetic marker-based studies with gene expression analyses, has exploded with the recent development of advanced microarray technologies. To account for systematic variation known to exist in microarray data, it is critical to properly normalize gene expression traits before performing genetic linkage analyses. However, imposing equal means and variances across pedigrees can over-correct for the true biological variation by ignoring familial correlations in expression values. We applied the robust multiarray average (RMA) method to gene expression trait data from 14 Centre d'Etude du Polymorphisme Humain (CEPH) Utah pedigrees provided by GAW15 (Genetic Analysis Workshop 15). We compared the RMA normalization method using within-pedigree pools to RMA normalization using all individuals in a single pool, which ignores pedigree membership, and investigated the effects of these different methods on 18 gene expression traits previously found to be linked to regions containing the corresponding structural locus. Familial correlation coefficients of the expressed traits were stronger when traits were normalized within pedigrees. Surprisingly, the linkage plots for these traits were similar, suggesting that although heritability increases when traits are normalized within pedigrees, the strength of linkage evidence does not necessarily change substantially. Normalization Method (dpeaa)DE-He213 Genetical Genomic (dpeaa)DE-He213 Normalization Pool (dpeaa)DE-He213 Familial Correlation (dpeaa)DE-He213 Robust Multiarray Average (dpeaa)DE-He213 Doan, Betty Q aut Duggal, Priya aut Bailey-Wilson, Joan E aut Enthalten in BMC proceedings London : BioMed Central, 2007 1(2007), Suppl 1 vom: 18. Dez. (DE-627)559080840 (DE-600)2411867-9 1753-6561 nnns volume:1 year:2007 number:Suppl 1 day:18 month:12 https://dx.doi.org/10.1186/1753-6561-1-S1-S152 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 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_2014 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 1 2007 Suppl 1 18 12 |
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normalization of microarray expression data using within-pedigree pool and its effect on linkage analysis |
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Normalization of microarray expression data using within-pedigree pool and its effect on linkage analysis |
abstract |
Abstract "Genetical genomics", the study of natural genetic variation combining data from genetic marker-based studies with gene expression analyses, has exploded with the recent development of advanced microarray technologies. To account for systematic variation known to exist in microarray data, it is critical to properly normalize gene expression traits before performing genetic linkage analyses. However, imposing equal means and variances across pedigrees can over-correct for the true biological variation by ignoring familial correlations in expression values. We applied the robust multiarray average (RMA) method to gene expression trait data from 14 Centre d'Etude du Polymorphisme Humain (CEPH) Utah pedigrees provided by GAW15 (Genetic Analysis Workshop 15). We compared the RMA normalization method using within-pedigree pools to RMA normalization using all individuals in a single pool, which ignores pedigree membership, and investigated the effects of these different methods on 18 gene expression traits previously found to be linked to regions containing the corresponding structural locus. Familial correlation coefficients of the expressed traits were stronger when traits were normalized within pedigrees. Surprisingly, the linkage plots for these traits were similar, suggesting that although heritability increases when traits are normalized within pedigrees, the strength of linkage evidence does not necessarily change substantially. © Kim et al; licensee BioMed Central Ltd. 2007. This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License ( |
abstractGer |
Abstract "Genetical genomics", the study of natural genetic variation combining data from genetic marker-based studies with gene expression analyses, has exploded with the recent development of advanced microarray technologies. To account for systematic variation known to exist in microarray data, it is critical to properly normalize gene expression traits before performing genetic linkage analyses. However, imposing equal means and variances across pedigrees can over-correct for the true biological variation by ignoring familial correlations in expression values. We applied the robust multiarray average (RMA) method to gene expression trait data from 14 Centre d'Etude du Polymorphisme Humain (CEPH) Utah pedigrees provided by GAW15 (Genetic Analysis Workshop 15). We compared the RMA normalization method using within-pedigree pools to RMA normalization using all individuals in a single pool, which ignores pedigree membership, and investigated the effects of these different methods on 18 gene expression traits previously found to be linked to regions containing the corresponding structural locus. Familial correlation coefficients of the expressed traits were stronger when traits were normalized within pedigrees. Surprisingly, the linkage plots for these traits were similar, suggesting that although heritability increases when traits are normalized within pedigrees, the strength of linkage evidence does not necessarily change substantially. © Kim et al; licensee BioMed Central Ltd. 2007. This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License ( |
abstract_unstemmed |
Abstract "Genetical genomics", the study of natural genetic variation combining data from genetic marker-based studies with gene expression analyses, has exploded with the recent development of advanced microarray technologies. To account for systematic variation known to exist in microarray data, it is critical to properly normalize gene expression traits before performing genetic linkage analyses. However, imposing equal means and variances across pedigrees can over-correct for the true biological variation by ignoring familial correlations in expression values. We applied the robust multiarray average (RMA) method to gene expression trait data from 14 Centre d'Etude du Polymorphisme Humain (CEPH) Utah pedigrees provided by GAW15 (Genetic Analysis Workshop 15). We compared the RMA normalization method using within-pedigree pools to RMA normalization using all individuals in a single pool, which ignores pedigree membership, and investigated the effects of these different methods on 18 gene expression traits previously found to be linked to regions containing the corresponding structural locus. Familial correlation coefficients of the expressed traits were stronger when traits were normalized within pedigrees. Surprisingly, the linkage plots for these traits were similar, suggesting that although heritability increases when traits are normalized within pedigrees, the strength of linkage evidence does not necessarily change substantially. © Kim et al; licensee BioMed Central Ltd. 2007. This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License ( |
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score |
7.400014 |