A procedure for the detection of linkage with high density SNP arrays in a large pedigree with colorectal cancer

<p<Abstract</p< <p<Background</p< <p<The apparent dominant model of colorectal cancer (CRC) inheritance in several large families, without mutations in known CRC susceptibility genes, suggests the presence of so far unidentified genes with strong or moderate effect on the development of CRC. Linkage analysis could lead to identification of susceptibility genes in such families. In comparison to classical linkage analysis with multi-allelic markers, single nucleotide polymorphism (SNP) arrays have increased information content and can be processed with higher throughput. Therefore, SNP arrays can be excellent tools for linkage analysis. However, the vast number of SNPs on the SNP arrays, combined with large informative pedigrees (e.g. <35–40 bits), presents us with a computational complexity that is challenging for existing statistical packages or even exceeds their capacity. We therefore setup a procedure for linkage analysis in large pedigrees and validated the method by genotyping using SNP arrays of a colorectal cancer family with a known <it<MLH1 </it<germ line mutation.</p< <p<Methods</p< <p<Quality control of the genotype data was performed in Alohomora, Mega2 and SimWalk2, with removal of uninformative SNPs, Mendelian inconsistencies and Mendelian consistent errors, respectively. Linkage disequilibrium was measured by SNPLINK and Merlin. Parametric linkage analysis using two flanking markers was performed using MENDEL. For multipoint parametric linkage analysis and haplotype analysis, SimWalk2 was used.</p< <p<Results</p< <p<On chromosome 3, in the <it<MLH1</it<-region, a LOD score of 1.9 was found by parametric linkage analysis using two flanking markers. On chromosome 11 a small region with LOD 1.1 was also detected. Upon linkage disequilibrium removal, multipoint linkage analysis yielded a LOD score of 2.1 in the <it<MLH1 </it<region, whereas the LOD score dropped to negative values in the region on chromosome 11. Subsequent haplotype analysis in the <it<MLH1 </it<region perfectly matched the mutation status of the family members.</p< <p<Conclusion</p< <p<We developed a workflow for linkage analysis in large families using high-density SNP arrays and validated this workflow in a family with colorectal cancer. Linkage disequilibrium has to be removed when using SNP arrays, because it can falsely inflate the LOD score. Haplotype analysis is adequate and can predict the carrier status of the family members.</p< Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Morreau Hans [verfasserIn] Devilee Peter [verfasserIn] Vasen Hans FA [verfasserIn] Tops Carli MJ [verfasserIn] van der Klift Heleen M [verfasserIn] Helmer Quinta [verfasserIn] Jagmohan-Changur Shantie [verfasserIn] Middeldorp Anneke [verfasserIn] Houwing-Duistermaat Jeanine J [verfasserIn] Wijnen Juul T [verfasserIn] van Wezel Tom [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2007

Übergeordnetes Werk:	In: BMC Cancer - BMC, 2003, 7(2007), 1, p 6
Übergeordnetes Werk:	volume:7 ; year:2007 ; number:1, p 6

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1186/1471-2407-7-6

Katalog-ID:	DOAJ037202170

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520			\|a <p<Abstract</p< <p<Background</p< <p<The apparent dominant model of colorectal cancer (CRC) inheritance in several large families, without mutations in known CRC susceptibility genes, suggests the presence of so far unidentified genes with strong or moderate effect on the development of CRC. Linkage analysis could lead to identification of susceptibility genes in such families. In comparison to classical linkage analysis with multi-allelic markers, single nucleotide polymorphism (SNP) arrays have increased information content and can be processed with higher throughput. Therefore, SNP arrays can be excellent tools for linkage analysis. However, the vast number of SNPs on the SNP arrays, combined with large informative pedigrees (e.g. <35–40 bits), presents us with a computational complexity that is challenging for existing statistical packages or even exceeds their capacity. We therefore setup a procedure for linkage analysis in large pedigrees and validated the method by genotyping using SNP arrays of a colorectal cancer family with a known <it<MLH1 </it<germ line mutation.</p< <p<Methods</p< <p<Quality control of the genotype data was performed in Alohomora, Mega2 and SimWalk2, with removal of uninformative SNPs, Mendelian inconsistencies and Mendelian consistent errors, respectively. Linkage disequilibrium was measured by SNPLINK and Merlin. Parametric linkage analysis using two flanking markers was performed using MENDEL. For multipoint parametric linkage analysis and haplotype analysis, SimWalk2 was used.</p< <p<Results</p< <p<On chromosome 3, in the <it<MLH1</it<-region, a LOD score of 1.9 was found by parametric linkage analysis using two flanking markers. On chromosome 11 a small region with LOD 1.1 was also detected. Upon linkage disequilibrium removal, multipoint linkage analysis yielded a LOD score of 2.1 in the <it<MLH1 </it<region, whereas the LOD score dropped to negative values in the region on chromosome 11. Subsequent haplotype analysis in the <it<MLH1 </it<region perfectly matched the mutation status of the family members.</p< <p<Conclusion</p< <p<We developed a workflow for linkage analysis in large families using high-density SNP arrays and validated this workflow in a family with colorectal cancer. Linkage disequilibrium has to be removed when using SNP arrays, because it can falsely inflate the LOD score. Haplotype analysis is adequate and can predict the carrier status of the family members.</p<
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700	0		\|a Jagmohan-Changur Shantie \|e verfasserin \|4 aut
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700	0		\|a Houwing-Duistermaat Jeanine J \|e verfasserin \|4 aut
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700	0		\|a van Wezel Tom \|e verfasserin \|4 aut
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912			\|a GBV_ILN_2014
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912			\|a GBV_ILN_2057
912			\|a GBV_ILN_2061
912			\|a GBV_ILN_2111
912			\|a GBV_ILN_2113
912			\|a GBV_ILN_2190
912			\|a GBV_ILN_4012
912			\|a GBV_ILN_4037
912			\|a GBV_ILN_4112
912			\|a GBV_ILN_4125
912			\|a GBV_ILN_4126
912			\|a GBV_ILN_4249
912			\|a GBV_ILN_4305
912			\|a GBV_ILN_4306
912			\|a GBV_ILN_4307
912			\|a GBV_ILN_4313
912			\|a GBV_ILN_4322
912			\|a GBV_ILN_4323
912			\|a GBV_ILN_4324
912			\|a GBV_ILN_4325
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Indexfelder

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matchkey_str	article:14712407:2007----::poeueoteeetoolnaeihihestsprasnlree
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allfields	10.1186/1471-2407-7-6 doi (DE-627)DOAJ037202170 (DE-599)DOAJafd428aa59fb4f9b80de4826372d8cf2 DE-627 ger DE-627 rakwb eng RC254-282 Morreau Hans verfasserin aut A procedure for the detection of linkage with high density SNP arrays in a large pedigree with colorectal cancer 2007 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier <p<Abstract</p< <p<Background</p< <p<The apparent dominant model of colorectal cancer (CRC) inheritance in several large families, without mutations in known CRC susceptibility genes, suggests the presence of so far unidentified genes with strong or moderate effect on the development of CRC. Linkage analysis could lead to identification of susceptibility genes in such families. In comparison to classical linkage analysis with multi-allelic markers, single nucleotide polymorphism (SNP) arrays have increased information content and can be processed with higher throughput. Therefore, SNP arrays can be excellent tools for linkage analysis. However, the vast number of SNPs on the SNP arrays, combined with large informative pedigrees (e.g. <35–40 bits), presents us with a computational complexity that is challenging for existing statistical packages or even exceeds their capacity. We therefore setup a procedure for linkage analysis in large pedigrees and validated the method by genotyping using SNP arrays of a colorectal cancer family with a known <it<MLH1 </it<germ line mutation.</p< <p<Methods</p< <p<Quality control of the genotype data was performed in Alohomora, Mega2 and SimWalk2, with removal of uninformative SNPs, Mendelian inconsistencies and Mendelian consistent errors, respectively. Linkage disequilibrium was measured by SNPLINK and Merlin. Parametric linkage analysis using two flanking markers was performed using MENDEL. For multipoint parametric linkage analysis and haplotype analysis, SimWalk2 was used.</p< <p<Results</p< <p<On chromosome 3, in the <it<MLH1</it<-region, a LOD score of 1.9 was found by parametric linkage analysis using two flanking markers. On chromosome 11 a small region with LOD 1.1 was also detected. Upon linkage disequilibrium removal, multipoint linkage analysis yielded a LOD score of 2.1 in the <it<MLH1 </it<region, whereas the LOD score dropped to negative values in the region on chromosome 11. Subsequent haplotype analysis in the <it<MLH1 </it<region perfectly matched the mutation status of the family members.</p< <p<Conclusion</p< <p<We developed a workflow for linkage analysis in large families using high-density SNP arrays and validated this workflow in a family with colorectal cancer. Linkage disequilibrium has to be removed when using SNP arrays, because it can falsely inflate the LOD score. Haplotype analysis is adequate and can predict the carrier status of the family members.</p< Neoplasms. Tumors. Oncology. Including cancer and carcinogens Devilee Peter verfasserin aut Vasen Hans FA verfasserin aut Tops Carli MJ verfasserin aut van der Klift Heleen M verfasserin aut Helmer Quinta verfasserin aut Jagmohan-Changur Shantie verfasserin aut Middeldorp Anneke verfasserin aut Houwing-Duistermaat Jeanine J verfasserin aut Wijnen Juul T verfasserin aut van Wezel Tom verfasserin aut In BMC Cancer BMC, 2003 7(2007), 1, p 6 (DE-627)326643710 (DE-600)2041352-X 14712407 nnns volume:7 year:2007 number:1, p 6 https://doi.org/10.1186/1471-2407-7-6 kostenfrei https://doaj.org/article/afd428aa59fb4f9b80de4826372d8cf2 kostenfrei http://www.biomedcentral.com/1471-2407/7/6 kostenfrei https://doaj.org/toc/1471-2407 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA 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_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 7 2007 1, p 6
spelling	10.1186/1471-2407-7-6 doi (DE-627)DOAJ037202170 (DE-599)DOAJafd428aa59fb4f9b80de4826372d8cf2 DE-627 ger DE-627 rakwb eng RC254-282 Morreau Hans verfasserin aut A procedure for the detection of linkage with high density SNP arrays in a large pedigree with colorectal cancer 2007 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier <p<Abstract</p< <p<Background</p< <p<The apparent dominant model of colorectal cancer (CRC) inheritance in several large families, without mutations in known CRC susceptibility genes, suggests the presence of so far unidentified genes with strong or moderate effect on the development of CRC. Linkage analysis could lead to identification of susceptibility genes in such families. In comparison to classical linkage analysis with multi-allelic markers, single nucleotide polymorphism (SNP) arrays have increased information content and can be processed with higher throughput. Therefore, SNP arrays can be excellent tools for linkage analysis. However, the vast number of SNPs on the SNP arrays, combined with large informative pedigrees (e.g. <35–40 bits), presents us with a computational complexity that is challenging for existing statistical packages or even exceeds their capacity. We therefore setup a procedure for linkage analysis in large pedigrees and validated the method by genotyping using SNP arrays of a colorectal cancer family with a known <it<MLH1 </it<germ line mutation.</p< <p<Methods</p< <p<Quality control of the genotype data was performed in Alohomora, Mega2 and SimWalk2, with removal of uninformative SNPs, Mendelian inconsistencies and Mendelian consistent errors, respectively. Linkage disequilibrium was measured by SNPLINK and Merlin. Parametric linkage analysis using two flanking markers was performed using MENDEL. For multipoint parametric linkage analysis and haplotype analysis, SimWalk2 was used.</p< <p<Results</p< <p<On chromosome 3, in the <it<MLH1</it<-region, a LOD score of 1.9 was found by parametric linkage analysis using two flanking markers. On chromosome 11 a small region with LOD 1.1 was also detected. Upon linkage disequilibrium removal, multipoint linkage analysis yielded a LOD score of 2.1 in the <it<MLH1 </it<region, whereas the LOD score dropped to negative values in the region on chromosome 11. Subsequent haplotype analysis in the <it<MLH1 </it<region perfectly matched the mutation status of the family members.</p< <p<Conclusion</p< <p<We developed a workflow for linkage analysis in large families using high-density SNP arrays and validated this workflow in a family with colorectal cancer. Linkage disequilibrium has to be removed when using SNP arrays, because it can falsely inflate the LOD score. Haplotype analysis is adequate and can predict the carrier status of the family members.</p< Neoplasms. Tumors. Oncology. Including cancer and carcinogens Devilee Peter verfasserin aut Vasen Hans FA verfasserin aut Tops Carli MJ verfasserin aut van der Klift Heleen M verfasserin aut Helmer Quinta verfasserin aut Jagmohan-Changur Shantie verfasserin aut Middeldorp Anneke verfasserin aut Houwing-Duistermaat Jeanine J verfasserin aut Wijnen Juul T verfasserin aut van Wezel Tom verfasserin aut In BMC Cancer BMC, 2003 7(2007), 1, p 6 (DE-627)326643710 (DE-600)2041352-X 14712407 nnns volume:7 year:2007 number:1, p 6 https://doi.org/10.1186/1471-2407-7-6 kostenfrei https://doaj.org/article/afd428aa59fb4f9b80de4826372d8cf2 kostenfrei http://www.biomedcentral.com/1471-2407/7/6 kostenfrei https://doaj.org/toc/1471-2407 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA 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_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 7 2007 1, p 6
allfields_unstemmed	10.1186/1471-2407-7-6 doi (DE-627)DOAJ037202170 (DE-599)DOAJafd428aa59fb4f9b80de4826372d8cf2 DE-627 ger DE-627 rakwb eng RC254-282 Morreau Hans verfasserin aut A procedure for the detection of linkage with high density SNP arrays in a large pedigree with colorectal cancer 2007 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier <p<Abstract</p< <p<Background</p< <p<The apparent dominant model of colorectal cancer (CRC) inheritance in several large families, without mutations in known CRC susceptibility genes, suggests the presence of so far unidentified genes with strong or moderate effect on the development of CRC. Linkage analysis could lead to identification of susceptibility genes in such families. In comparison to classical linkage analysis with multi-allelic markers, single nucleotide polymorphism (SNP) arrays have increased information content and can be processed with higher throughput. Therefore, SNP arrays can be excellent tools for linkage analysis. However, the vast number of SNPs on the SNP arrays, combined with large informative pedigrees (e.g. <35–40 bits), presents us with a computational complexity that is challenging for existing statistical packages or even exceeds their capacity. We therefore setup a procedure for linkage analysis in large pedigrees and validated the method by genotyping using SNP arrays of a colorectal cancer family with a known <it<MLH1 </it<germ line mutation.</p< <p<Methods</p< <p<Quality control of the genotype data was performed in Alohomora, Mega2 and SimWalk2, with removal of uninformative SNPs, Mendelian inconsistencies and Mendelian consistent errors, respectively. Linkage disequilibrium was measured by SNPLINK and Merlin. Parametric linkage analysis using two flanking markers was performed using MENDEL. For multipoint parametric linkage analysis and haplotype analysis, SimWalk2 was used.</p< <p<Results</p< <p<On chromosome 3, in the <it<MLH1</it<-region, a LOD score of 1.9 was found by parametric linkage analysis using two flanking markers. On chromosome 11 a small region with LOD 1.1 was also detected. Upon linkage disequilibrium removal, multipoint linkage analysis yielded a LOD score of 2.1 in the <it<MLH1 </it<region, whereas the LOD score dropped to negative values in the region on chromosome 11. Subsequent haplotype analysis in the <it<MLH1 </it<region perfectly matched the mutation status of the family members.</p< <p<Conclusion</p< <p<We developed a workflow for linkage analysis in large families using high-density SNP arrays and validated this workflow in a family with colorectal cancer. Linkage disequilibrium has to be removed when using SNP arrays, because it can falsely inflate the LOD score. Haplotype analysis is adequate and can predict the carrier status of the family members.</p< Neoplasms. Tumors. Oncology. Including cancer and carcinogens Devilee Peter verfasserin aut Vasen Hans FA verfasserin aut Tops Carli MJ verfasserin aut van der Klift Heleen M verfasserin aut Helmer Quinta verfasserin aut Jagmohan-Changur Shantie verfasserin aut Middeldorp Anneke verfasserin aut Houwing-Duistermaat Jeanine J verfasserin aut Wijnen Juul T verfasserin aut van Wezel Tom verfasserin aut In BMC Cancer BMC, 2003 7(2007), 1, p 6 (DE-627)326643710 (DE-600)2041352-X 14712407 nnns volume:7 year:2007 number:1, p 6 https://doi.org/10.1186/1471-2407-7-6 kostenfrei https://doaj.org/article/afd428aa59fb4f9b80de4826372d8cf2 kostenfrei http://www.biomedcentral.com/1471-2407/7/6 kostenfrei https://doaj.org/toc/1471-2407 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA 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_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 7 2007 1, p 6
allfieldsGer	10.1186/1471-2407-7-6 doi (DE-627)DOAJ037202170 (DE-599)DOAJafd428aa59fb4f9b80de4826372d8cf2 DE-627 ger DE-627 rakwb eng RC254-282 Morreau Hans verfasserin aut A procedure for the detection of linkage with high density SNP arrays in a large pedigree with colorectal cancer 2007 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier <p<Abstract</p< <p<Background</p< <p<The apparent dominant model of colorectal cancer (CRC) inheritance in several large families, without mutations in known CRC susceptibility genes, suggests the presence of so far unidentified genes with strong or moderate effect on the development of CRC. Linkage analysis could lead to identification of susceptibility genes in such families. In comparison to classical linkage analysis with multi-allelic markers, single nucleotide polymorphism (SNP) arrays have increased information content and can be processed with higher throughput. Therefore, SNP arrays can be excellent tools for linkage analysis. However, the vast number of SNPs on the SNP arrays, combined with large informative pedigrees (e.g. <35–40 bits), presents us with a computational complexity that is challenging for existing statistical packages or even exceeds their capacity. We therefore setup a procedure for linkage analysis in large pedigrees and validated the method by genotyping using SNP arrays of a colorectal cancer family with a known <it<MLH1 </it<germ line mutation.</p< <p<Methods</p< <p<Quality control of the genotype data was performed in Alohomora, Mega2 and SimWalk2, with removal of uninformative SNPs, Mendelian inconsistencies and Mendelian consistent errors, respectively. Linkage disequilibrium was measured by SNPLINK and Merlin. Parametric linkage analysis using two flanking markers was performed using MENDEL. For multipoint parametric linkage analysis and haplotype analysis, SimWalk2 was used.</p< <p<Results</p< <p<On chromosome 3, in the <it<MLH1</it<-region, a LOD score of 1.9 was found by parametric linkage analysis using two flanking markers. On chromosome 11 a small region with LOD 1.1 was also detected. Upon linkage disequilibrium removal, multipoint linkage analysis yielded a LOD score of 2.1 in the <it<MLH1 </it<region, whereas the LOD score dropped to negative values in the region on chromosome 11. Subsequent haplotype analysis in the <it<MLH1 </it<region perfectly matched the mutation status of the family members.</p< <p<Conclusion</p< <p<We developed a workflow for linkage analysis in large families using high-density SNP arrays and validated this workflow in a family with colorectal cancer. Linkage disequilibrium has to be removed when using SNP arrays, because it can falsely inflate the LOD score. Haplotype analysis is adequate and can predict the carrier status of the family members.</p< Neoplasms. Tumors. Oncology. Including cancer and carcinogens Devilee Peter verfasserin aut Vasen Hans FA verfasserin aut Tops Carli MJ verfasserin aut van der Klift Heleen M verfasserin aut Helmer Quinta verfasserin aut Jagmohan-Changur Shantie verfasserin aut Middeldorp Anneke verfasserin aut Houwing-Duistermaat Jeanine J verfasserin aut Wijnen Juul T verfasserin aut van Wezel Tom verfasserin aut In BMC Cancer BMC, 2003 7(2007), 1, p 6 (DE-627)326643710 (DE-600)2041352-X 14712407 nnns volume:7 year:2007 number:1, p 6 https://doi.org/10.1186/1471-2407-7-6 kostenfrei https://doaj.org/article/afd428aa59fb4f9b80de4826372d8cf2 kostenfrei http://www.biomedcentral.com/1471-2407/7/6 kostenfrei https://doaj.org/toc/1471-2407 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA 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_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 7 2007 1, p 6
allfieldsSound	10.1186/1471-2407-7-6 doi (DE-627)DOAJ037202170 (DE-599)DOAJafd428aa59fb4f9b80de4826372d8cf2 DE-627 ger DE-627 rakwb eng RC254-282 Morreau Hans verfasserin aut A procedure for the detection of linkage with high density SNP arrays in a large pedigree with colorectal cancer 2007 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier <p<Abstract</p< <p<Background</p< <p<The apparent dominant model of colorectal cancer (CRC) inheritance in several large families, without mutations in known CRC susceptibility genes, suggests the presence of so far unidentified genes with strong or moderate effect on the development of CRC. Linkage analysis could lead to identification of susceptibility genes in such families. In comparison to classical linkage analysis with multi-allelic markers, single nucleotide polymorphism (SNP) arrays have increased information content and can be processed with higher throughput. Therefore, SNP arrays can be excellent tools for linkage analysis. However, the vast number of SNPs on the SNP arrays, combined with large informative pedigrees (e.g. <35–40 bits), presents us with a computational complexity that is challenging for existing statistical packages or even exceeds their capacity. We therefore setup a procedure for linkage analysis in large pedigrees and validated the method by genotyping using SNP arrays of a colorectal cancer family with a known <it<MLH1 </it<germ line mutation.</p< <p<Methods</p< <p<Quality control of the genotype data was performed in Alohomora, Mega2 and SimWalk2, with removal of uninformative SNPs, Mendelian inconsistencies and Mendelian consistent errors, respectively. Linkage disequilibrium was measured by SNPLINK and Merlin. Parametric linkage analysis using two flanking markers was performed using MENDEL. For multipoint parametric linkage analysis and haplotype analysis, SimWalk2 was used.</p< <p<Results</p< <p<On chromosome 3, in the <it<MLH1</it<-region, a LOD score of 1.9 was found by parametric linkage analysis using two flanking markers. On chromosome 11 a small region with LOD 1.1 was also detected. Upon linkage disequilibrium removal, multipoint linkage analysis yielded a LOD score of 2.1 in the <it<MLH1 </it<region, whereas the LOD score dropped to negative values in the region on chromosome 11. Subsequent haplotype analysis in the <it<MLH1 </it<region perfectly matched the mutation status of the family members.</p< <p<Conclusion</p< <p<We developed a workflow for linkage analysis in large families using high-density SNP arrays and validated this workflow in a family with colorectal cancer. Linkage disequilibrium has to be removed when using SNP arrays, because it can falsely inflate the LOD score. Haplotype analysis is adequate and can predict the carrier status of the family members.</p< Neoplasms. Tumors. Oncology. Including cancer and carcinogens Devilee Peter verfasserin aut Vasen Hans FA verfasserin aut Tops Carli MJ verfasserin aut van der Klift Heleen M verfasserin aut Helmer Quinta verfasserin aut Jagmohan-Changur Shantie verfasserin aut Middeldorp Anneke verfasserin aut Houwing-Duistermaat Jeanine J verfasserin aut Wijnen Juul T verfasserin aut van Wezel Tom verfasserin aut In BMC Cancer BMC, 2003 7(2007), 1, p 6 (DE-627)326643710 (DE-600)2041352-X 14712407 nnns volume:7 year:2007 number:1, p 6 https://doi.org/10.1186/1471-2407-7-6 kostenfrei https://doaj.org/article/afd428aa59fb4f9b80de4826372d8cf2 kostenfrei http://www.biomedcentral.com/1471-2407/7/6 kostenfrei https://doaj.org/toc/1471-2407 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA 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_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 7 2007 1, p 6
language	English
source	In BMC Cancer 7(2007), 1, p 6 volume:7 year:2007 number:1, p 6
sourceStr	In BMC Cancer 7(2007), 1, p 6 volume:7 year:2007 number:1, p 6
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Neoplasms. Tumors. Oncology. Including cancer and carcinogens
isfreeaccess_bool	true
container_title	BMC Cancer
authorswithroles_txt_mv	Morreau Hans @@aut@@ Devilee Peter @@aut@@ Vasen Hans FA @@aut@@ Tops Carli MJ @@aut@@ van der Klift Heleen M @@aut@@ Helmer Quinta @@aut@@ Jagmohan-Changur Shantie @@aut@@ Middeldorp Anneke @@aut@@ Houwing-Duistermaat Jeanine J @@aut@@ Wijnen Juul T @@aut@@ van Wezel Tom @@aut@@
publishDateDaySort_date	2007-01-01T00:00:00Z
hierarchy_top_id	326643710
id	DOAJ037202170
language_de	englisch
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Linkage analysis could lead to identification of susceptibility genes in such families. In comparison to classical linkage analysis with multi-allelic markers, single nucleotide polymorphism (SNP) arrays have increased information content and can be processed with higher throughput. Therefore, SNP arrays can be excellent tools for linkage analysis. However, the vast number of SNPs on the SNP arrays, combined with large informative pedigrees (e.g. <35–40 bits), presents us with a computational complexity that is challenging for existing statistical packages or even exceeds their capacity. We therefore setup a procedure for linkage analysis in large pedigrees and validated the method by genotyping using SNP arrays of a colorectal cancer family with a known <it<MLH1 </it<germ line mutation.</p< <p<Methods</p< <p<Quality control of the genotype data was performed in Alohomora, Mega2 and SimWalk2, with removal of uninformative SNPs, Mendelian inconsistencies and Mendelian consistent errors, respectively. Linkage disequilibrium was measured by SNPLINK and Merlin. Parametric linkage analysis using two flanking markers was performed using MENDEL. For multipoint parametric linkage analysis and haplotype analysis, SimWalk2 was used.</p< <p<Results</p< <p<On chromosome 3, in the <it<MLH1</it<-region, a LOD score of 1.9 was found by parametric linkage analysis using two flanking markers. On chromosome 11 a small region with LOD 1.1 was also detected. 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callnumber-first	R - Medicine
author	Morreau Hans
spellingShingle	Morreau Hans misc RC254-282 misc Neoplasms. Tumors. Oncology. Including cancer and carcinogens A procedure for the detection of linkage with high density SNP arrays in a large pedigree with colorectal cancer
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topic_title	RC254-282 A procedure for the detection of linkage with high density SNP arrays in a large pedigree with colorectal cancer
topic	misc RC254-282 misc Neoplasms. Tumors. Oncology. Including cancer and carcinogens
topic_unstemmed	misc RC254-282 misc Neoplasms. Tumors. Oncology. Including cancer and carcinogens
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title	A procedure for the detection of linkage with high density SNP arrays in a large pedigree with colorectal cancer
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title_full	A procedure for the detection of linkage with high density SNP arrays in a large pedigree with colorectal cancer
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author_browse	Morreau Hans Devilee Peter Vasen Hans FA Tops Carli MJ van der Klift Heleen M Helmer Quinta Jagmohan-Changur Shantie Middeldorp Anneke Houwing-Duistermaat Jeanine J Wijnen Juul T van Wezel Tom
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title_sort	procedure for the detection of linkage with high density snp arrays in a large pedigree with colorectal cancer
callnumber	RC254-282
title_auth	A procedure for the detection of linkage with high density SNP arrays in a large pedigree with colorectal cancer
abstract	<p<Abstract</p< <p<Background</p< <p<The apparent dominant model of colorectal cancer (CRC) inheritance in several large families, without mutations in known CRC susceptibility genes, suggests the presence of so far unidentified genes with strong or moderate effect on the development of CRC. Linkage analysis could lead to identification of susceptibility genes in such families. In comparison to classical linkage analysis with multi-allelic markers, single nucleotide polymorphism (SNP) arrays have increased information content and can be processed with higher throughput. Therefore, SNP arrays can be excellent tools for linkage analysis. However, the vast number of SNPs on the SNP arrays, combined with large informative pedigrees (e.g. <35–40 bits), presents us with a computational complexity that is challenging for existing statistical packages or even exceeds their capacity. We therefore setup a procedure for linkage analysis in large pedigrees and validated the method by genotyping using SNP arrays of a colorectal cancer family with a known <it<MLH1 </it<germ line mutation.</p< <p<Methods</p< <p<Quality control of the genotype data was performed in Alohomora, Mega2 and SimWalk2, with removal of uninformative SNPs, Mendelian inconsistencies and Mendelian consistent errors, respectively. Linkage disequilibrium was measured by SNPLINK and Merlin. Parametric linkage analysis using two flanking markers was performed using MENDEL. For multipoint parametric linkage analysis and haplotype analysis, SimWalk2 was used.</p< <p<Results</p< <p<On chromosome 3, in the <it<MLH1</it<-region, a LOD score of 1.9 was found by parametric linkage analysis using two flanking markers. On chromosome 11 a small region with LOD 1.1 was also detected. Upon linkage disequilibrium removal, multipoint linkage analysis yielded a LOD score of 2.1 in the <it<MLH1 </it<region, whereas the LOD score dropped to negative values in the region on chromosome 11. Subsequent haplotype analysis in the <it<MLH1 </it<region perfectly matched the mutation status of the family members.</p< <p<Conclusion</p< <p<We developed a workflow for linkage analysis in large families using high-density SNP arrays and validated this workflow in a family with colorectal cancer. Linkage disequilibrium has to be removed when using SNP arrays, because it can falsely inflate the LOD score. Haplotype analysis is adequate and can predict the carrier status of the family members.</p<
abstractGer	<p<Abstract</p< <p<Background</p< <p<The apparent dominant model of colorectal cancer (CRC) inheritance in several large families, without mutations in known CRC susceptibility genes, suggests the presence of so far unidentified genes with strong or moderate effect on the development of CRC. Linkage analysis could lead to identification of susceptibility genes in such families. In comparison to classical linkage analysis with multi-allelic markers, single nucleotide polymorphism (SNP) arrays have increased information content and can be processed with higher throughput. Therefore, SNP arrays can be excellent tools for linkage analysis. However, the vast number of SNPs on the SNP arrays, combined with large informative pedigrees (e.g. <35–40 bits), presents us with a computational complexity that is challenging for existing statistical packages or even exceeds their capacity. We therefore setup a procedure for linkage analysis in large pedigrees and validated the method by genotyping using SNP arrays of a colorectal cancer family with a known <it<MLH1 </it<germ line mutation.</p< <p<Methods</p< <p<Quality control of the genotype data was performed in Alohomora, Mega2 and SimWalk2, with removal of uninformative SNPs, Mendelian inconsistencies and Mendelian consistent errors, respectively. Linkage disequilibrium was measured by SNPLINK and Merlin. Parametric linkage analysis using two flanking markers was performed using MENDEL. For multipoint parametric linkage analysis and haplotype analysis, SimWalk2 was used.</p< <p<Results</p< <p<On chromosome 3, in the <it<MLH1</it<-region, a LOD score of 1.9 was found by parametric linkage analysis using two flanking markers. On chromosome 11 a small region with LOD 1.1 was also detected. Upon linkage disequilibrium removal, multipoint linkage analysis yielded a LOD score of 2.1 in the <it<MLH1 </it<region, whereas the LOD score dropped to negative values in the region on chromosome 11. Subsequent haplotype analysis in the <it<MLH1 </it<region perfectly matched the mutation status of the family members.</p< <p<Conclusion</p< <p<We developed a workflow for linkage analysis in large families using high-density SNP arrays and validated this workflow in a family with colorectal cancer. Linkage disequilibrium has to be removed when using SNP arrays, because it can falsely inflate the LOD score. Haplotype analysis is adequate and can predict the carrier status of the family members.</p<
abstract_unstemmed	<p<Abstract</p< <p<Background</p< <p<The apparent dominant model of colorectal cancer (CRC) inheritance in several large families, without mutations in known CRC susceptibility genes, suggests the presence of so far unidentified genes with strong or moderate effect on the development of CRC. Linkage analysis could lead to identification of susceptibility genes in such families. In comparison to classical linkage analysis with multi-allelic markers, single nucleotide polymorphism (SNP) arrays have increased information content and can be processed with higher throughput. Therefore, SNP arrays can be excellent tools for linkage analysis. However, the vast number of SNPs on the SNP arrays, combined with large informative pedigrees (e.g. <35–40 bits), presents us with a computational complexity that is challenging for existing statistical packages or even exceeds their capacity. We therefore setup a procedure for linkage analysis in large pedigrees and validated the method by genotyping using SNP arrays of a colorectal cancer family with a known <it<MLH1 </it<germ line mutation.</p< <p<Methods</p< <p<Quality control of the genotype data was performed in Alohomora, Mega2 and SimWalk2, with removal of uninformative SNPs, Mendelian inconsistencies and Mendelian consistent errors, respectively. Linkage disequilibrium was measured by SNPLINK and Merlin. Parametric linkage analysis using two flanking markers was performed using MENDEL. For multipoint parametric linkage analysis and haplotype analysis, SimWalk2 was used.</p< <p<Results</p< <p<On chromosome 3, in the <it<MLH1</it<-region, a LOD score of 1.9 was found by parametric linkage analysis using two flanking markers. On chromosome 11 a small region with LOD 1.1 was also detected. Upon linkage disequilibrium removal, multipoint linkage analysis yielded a LOD score of 2.1 in the <it<MLH1 </it<region, whereas the LOD score dropped to negative values in the region on chromosome 11. Subsequent haplotype analysis in the <it<MLH1 </it<region perfectly matched the mutation status of the family members.</p< <p<Conclusion</p< <p<We developed a workflow for linkage analysis in large families using high-density SNP arrays and validated this workflow in a family with colorectal cancer. Linkage disequilibrium has to be removed when using SNP arrays, because it can falsely inflate the LOD score. Haplotype analysis is adequate and can predict the carrier status of the family members.</p<
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title_short	A procedure for the detection of linkage with high density SNP arrays in a large pedigree with colorectal cancer
url	https://doi.org/10.1186/1471-2407-7-6 https://doaj.org/article/afd428aa59fb4f9b80de4826372d8cf2 http://www.biomedcentral.com/1471-2407/7/6 https://doaj.org/toc/1471-2407
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Linkage analysis could lead to identification of susceptibility genes in such families. In comparison to classical linkage analysis with multi-allelic markers, single nucleotide polymorphism (SNP) arrays have increased information content and can be processed with higher throughput. Therefore, SNP arrays can be excellent tools for linkage analysis. However, the vast number of SNPs on the SNP arrays, combined with large informative pedigrees (e.g. <35–40 bits), presents us with a computational complexity that is challenging for existing statistical packages or even exceeds their capacity. We therefore setup a procedure for linkage analysis in large pedigrees and validated the method by genotyping using SNP arrays of a colorectal cancer family with a known <it<MLH1 </it<germ line mutation.</p< <p<Methods</p< <p<Quality control of the genotype data was performed in Alohomora, Mega2 and SimWalk2, with removal of uninformative SNPs, Mendelian inconsistencies and Mendelian consistent errors, respectively. Linkage disequilibrium was measured by SNPLINK and Merlin. Parametric linkage analysis using two flanking markers was performed using MENDEL. For multipoint parametric linkage analysis and haplotype analysis, SimWalk2 was used.</p< <p<Results</p< <p<On chromosome 3, in the <it<MLH1</it<-region, a LOD score of 1.9 was found by parametric linkage analysis using two flanking markers. On chromosome 11 a small region with LOD 1.1 was also detected. Upon linkage disequilibrium removal, multipoint linkage analysis yielded a LOD score of 2.1 in the <it<MLH1 </it<region, whereas the LOD score dropped to negative values in the region on chromosome 11. Subsequent haplotype analysis in the <it<MLH1 </it<region perfectly matched the mutation status of the family members.</p< <p<Conclusion</p< <p<We developed a workflow for linkage analysis in large families using high-density SNP arrays and validated this workflow in a family with colorectal cancer. Linkage disequilibrium has to be removed when using SNP arrays, because it can falsely inflate the LOD score. Haplotype analysis is adequate and can predict the carrier status of the family members.</p<</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Neoplasms. Tumors. Oncology. 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A procedure for the detection of linkage with high density SNP arrays in a large pedigree with colorectal cancer

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