Rare variant association analysis in case-parents studies by allowing for missing parental genotypes

Background The development of next-generation sequencing technologies has facilitated the identification of rare variants. Family-based design is commonly used to effectively control for population admixture and substructure, which is more prominent for rare variants. Case-parents studies, as typica...
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Autor*in:	Li, Yumei [verfasserIn] Xiang, Yang Xu, Chao Shen, Hui Deng, Hongwen

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2018

Schlagwörter:	Rare-variant association analysis Case-parent trios Collapsing method

Anmerkung:	© The Author(s). 2018

Übergeordnetes Werk:	Enthalten in: BMC genetics - London : BioMed Central, 2000, 19(2018), 1 vom: 15. Jan.
Übergeordnetes Werk:	volume:19 ; year:2018 ; number:1 ; day:15 ; month:01

Links:	Volltext

DOI / URN:	10.1186/s12863-018-0597-8

Katalog-ID:	SPR027017656

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520			\|a Background The development of next-generation sequencing technologies has facilitated the identification of rare variants. Family-based design is commonly used to effectively control for population admixture and substructure, which is more prominent for rare variants. Case-parents studies, as typical strategies in family-based design, are widely used in rare variant-disease association analysis. Current methods in case-parents studies are based on complete case-parents data; however, parental genotypes may be missing in case-parents trios, and removing these data may lead to a loss in statistical power. The present study focuses on testing for rare variant-disease association in case-parents study by allowing for missing parental genotypes. Results In this report, we extended the collapsing method for rare variant association analysis in case-parents studies to allow for missing parental genotypes, and investigated the performance of two methods by using the difference of genotypes between affected offspring and their corresponding “complements” in case-parent trios and TDT framework. Using simulations, we showed that, compared with the methods just only using complete case-parents data, the proposed strategy allowing for missing parental genotypes, or even adding unrelated affected individuals, can greatly improve the statistical power and meanwhile is not affected by population stratification. Conclusions We conclude that adding case-parents data with missing parental genotypes to complete case-parents data set can greatly improve the power of our strategy for rare variant-disease association.
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Indexfelder

author_variant	y l yl y x yx c x cx h s hs h d hd
matchkey_str	article:14712156:2018----::aeainascainnlssnaeaetsuisyloigo
hierarchy_sort_str	2018
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allfields	10.1186/s12863-018-0597-8 doi (DE-627)SPR027017656 (SPR)s12863-018-0597-8-e DE-627 ger DE-627 rakwb eng Li, Yumei verfasserin (orcid)0000-0003-1755-4504 aut Rare variant association analysis in case-parents studies by allowing for missing parental genotypes 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2018 Background The development of next-generation sequencing technologies has facilitated the identification of rare variants. Family-based design is commonly used to effectively control for population admixture and substructure, which is more prominent for rare variants. Case-parents studies, as typical strategies in family-based design, are widely used in rare variant-disease association analysis. Current methods in case-parents studies are based on complete case-parents data; however, parental genotypes may be missing in case-parents trios, and removing these data may lead to a loss in statistical power. The present study focuses on testing for rare variant-disease association in case-parents study by allowing for missing parental genotypes. Results In this report, we extended the collapsing method for rare variant association analysis in case-parents studies to allow for missing parental genotypes, and investigated the performance of two methods by using the difference of genotypes between affected offspring and their corresponding “complements” in case-parent trios and TDT framework. Using simulations, we showed that, compared with the methods just only using complete case-parents data, the proposed strategy allowing for missing parental genotypes, or even adding unrelated affected individuals, can greatly improve the statistical power and meanwhile is not affected by population stratification. Conclusions We conclude that adding case-parents data with missing parental genotypes to complete case-parents data set can greatly improve the power of our strategy for rare variant-disease association. Rare-variant association analysis (dpeaa)DE-He213 Case-parent trios (dpeaa)DE-He213 Collapsing method (dpeaa)DE-He213 Xiang, Yang aut Xu, Chao aut Shen, Hui aut Deng, Hongwen aut Enthalten in BMC genetics London : BioMed Central, 2000 19(2018), 1 vom: 15. Jan. (DE-627)326644938 (DE-600)2041497-3 1471-2156 nnns volume:19 year:2018 number:1 day:15 month:01 https://dx.doi.org/10.1186/s12863-018-0597-8 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_31 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 19 2018 1 15 01
spelling	10.1186/s12863-018-0597-8 doi (DE-627)SPR027017656 (SPR)s12863-018-0597-8-e DE-627 ger DE-627 rakwb eng Li, Yumei verfasserin (orcid)0000-0003-1755-4504 aut Rare variant association analysis in case-parents studies by allowing for missing parental genotypes 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2018 Background The development of next-generation sequencing technologies has facilitated the identification of rare variants. Family-based design is commonly used to effectively control for population admixture and substructure, which is more prominent for rare variants. Case-parents studies, as typical strategies in family-based design, are widely used in rare variant-disease association analysis. Current methods in case-parents studies are based on complete case-parents data; however, parental genotypes may be missing in case-parents trios, and removing these data may lead to a loss in statistical power. The present study focuses on testing for rare variant-disease association in case-parents study by allowing for missing parental genotypes. Results In this report, we extended the collapsing method for rare variant association analysis in case-parents studies to allow for missing parental genotypes, and investigated the performance of two methods by using the difference of genotypes between affected offspring and their corresponding “complements” in case-parent trios and TDT framework. Using simulations, we showed that, compared with the methods just only using complete case-parents data, the proposed strategy allowing for missing parental genotypes, or even adding unrelated affected individuals, can greatly improve the statistical power and meanwhile is not affected by population stratification. Conclusions We conclude that adding case-parents data with missing parental genotypes to complete case-parents data set can greatly improve the power of our strategy for rare variant-disease association. Rare-variant association analysis (dpeaa)DE-He213 Case-parent trios (dpeaa)DE-He213 Collapsing method (dpeaa)DE-He213 Xiang, Yang aut Xu, Chao aut Shen, Hui aut Deng, Hongwen aut Enthalten in BMC genetics London : BioMed Central, 2000 19(2018), 1 vom: 15. Jan. (DE-627)326644938 (DE-600)2041497-3 1471-2156 nnns volume:19 year:2018 number:1 day:15 month:01 https://dx.doi.org/10.1186/s12863-018-0597-8 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_31 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 19 2018 1 15 01
allfields_unstemmed	10.1186/s12863-018-0597-8 doi (DE-627)SPR027017656 (SPR)s12863-018-0597-8-e DE-627 ger DE-627 rakwb eng Li, Yumei verfasserin (orcid)0000-0003-1755-4504 aut Rare variant association analysis in case-parents studies by allowing for missing parental genotypes 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2018 Background The development of next-generation sequencing technologies has facilitated the identification of rare variants. Family-based design is commonly used to effectively control for population admixture and substructure, which is more prominent for rare variants. Case-parents studies, as typical strategies in family-based design, are widely used in rare variant-disease association analysis. Current methods in case-parents studies are based on complete case-parents data; however, parental genotypes may be missing in case-parents trios, and removing these data may lead to a loss in statistical power. The present study focuses on testing for rare variant-disease association in case-parents study by allowing for missing parental genotypes. Results In this report, we extended the collapsing method for rare variant association analysis in case-parents studies to allow for missing parental genotypes, and investigated the performance of two methods by using the difference of genotypes between affected offspring and their corresponding “complements” in case-parent trios and TDT framework. Using simulations, we showed that, compared with the methods just only using complete case-parents data, the proposed strategy allowing for missing parental genotypes, or even adding unrelated affected individuals, can greatly improve the statistical power and meanwhile is not affected by population stratification. Conclusions We conclude that adding case-parents data with missing parental genotypes to complete case-parents data set can greatly improve the power of our strategy for rare variant-disease association. Rare-variant association analysis (dpeaa)DE-He213 Case-parent trios (dpeaa)DE-He213 Collapsing method (dpeaa)DE-He213 Xiang, Yang aut Xu, Chao aut Shen, Hui aut Deng, Hongwen aut Enthalten in BMC genetics London : BioMed Central, 2000 19(2018), 1 vom: 15. Jan. (DE-627)326644938 (DE-600)2041497-3 1471-2156 nnns volume:19 year:2018 number:1 day:15 month:01 https://dx.doi.org/10.1186/s12863-018-0597-8 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_31 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 19 2018 1 15 01
allfieldsGer	10.1186/s12863-018-0597-8 doi (DE-627)SPR027017656 (SPR)s12863-018-0597-8-e DE-627 ger DE-627 rakwb eng Li, Yumei verfasserin (orcid)0000-0003-1755-4504 aut Rare variant association analysis in case-parents studies by allowing for missing parental genotypes 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2018 Background The development of next-generation sequencing technologies has facilitated the identification of rare variants. Family-based design is commonly used to effectively control for population admixture and substructure, which is more prominent for rare variants. Case-parents studies, as typical strategies in family-based design, are widely used in rare variant-disease association analysis. Current methods in case-parents studies are based on complete case-parents data; however, parental genotypes may be missing in case-parents trios, and removing these data may lead to a loss in statistical power. The present study focuses on testing for rare variant-disease association in case-parents study by allowing for missing parental genotypes. Results In this report, we extended the collapsing method for rare variant association analysis in case-parents studies to allow for missing parental genotypes, and investigated the performance of two methods by using the difference of genotypes between affected offspring and their corresponding “complements” in case-parent trios and TDT framework. Using simulations, we showed that, compared with the methods just only using complete case-parents data, the proposed strategy allowing for missing parental genotypes, or even adding unrelated affected individuals, can greatly improve the statistical power and meanwhile is not affected by population stratification. Conclusions We conclude that adding case-parents data with missing parental genotypes to complete case-parents data set can greatly improve the power of our strategy for rare variant-disease association. Rare-variant association analysis (dpeaa)DE-He213 Case-parent trios (dpeaa)DE-He213 Collapsing method (dpeaa)DE-He213 Xiang, Yang aut Xu, Chao aut Shen, Hui aut Deng, Hongwen aut Enthalten in BMC genetics London : BioMed Central, 2000 19(2018), 1 vom: 15. Jan. (DE-627)326644938 (DE-600)2041497-3 1471-2156 nnns volume:19 year:2018 number:1 day:15 month:01 https://dx.doi.org/10.1186/s12863-018-0597-8 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_31 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 19 2018 1 15 01
allfieldsSound	10.1186/s12863-018-0597-8 doi (DE-627)SPR027017656 (SPR)s12863-018-0597-8-e DE-627 ger DE-627 rakwb eng Li, Yumei verfasserin (orcid)0000-0003-1755-4504 aut Rare variant association analysis in case-parents studies by allowing for missing parental genotypes 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2018 Background The development of next-generation sequencing technologies has facilitated the identification of rare variants. Family-based design is commonly used to effectively control for population admixture and substructure, which is more prominent for rare variants. Case-parents studies, as typical strategies in family-based design, are widely used in rare variant-disease association analysis. Current methods in case-parents studies are based on complete case-parents data; however, parental genotypes may be missing in case-parents trios, and removing these data may lead to a loss in statistical power. The present study focuses on testing for rare variant-disease association in case-parents study by allowing for missing parental genotypes. Results In this report, we extended the collapsing method for rare variant association analysis in case-parents studies to allow for missing parental genotypes, and investigated the performance of two methods by using the difference of genotypes between affected offspring and their corresponding “complements” in case-parent trios and TDT framework. Using simulations, we showed that, compared with the methods just only using complete case-parents data, the proposed strategy allowing for missing parental genotypes, or even adding unrelated affected individuals, can greatly improve the statistical power and meanwhile is not affected by population stratification. Conclusions We conclude that adding case-parents data with missing parental genotypes to complete case-parents data set can greatly improve the power of our strategy for rare variant-disease association. Rare-variant association analysis (dpeaa)DE-He213 Case-parent trios (dpeaa)DE-He213 Collapsing method (dpeaa)DE-He213 Xiang, Yang aut Xu, Chao aut Shen, Hui aut Deng, Hongwen aut Enthalten in BMC genetics London : BioMed Central, 2000 19(2018), 1 vom: 15. Jan. (DE-627)326644938 (DE-600)2041497-3 1471-2156 nnns volume:19 year:2018 number:1 day:15 month:01 https://dx.doi.org/10.1186/s12863-018-0597-8 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_31 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 19 2018 1 15 01
language	English
source	Enthalten in BMC genetics 19(2018), 1 vom: 15. Jan. volume:19 year:2018 number:1 day:15 month:01
sourceStr	Enthalten in BMC genetics 19(2018), 1 vom: 15. Jan. volume:19 year:2018 number:1 day:15 month:01
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Rare-variant association analysis Case-parent trios Collapsing method
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author	Li, Yumei
spellingShingle	Li, Yumei misc Rare-variant association analysis misc Case-parent trios misc Collapsing method Rare variant association analysis in case-parents studies by allowing for missing parental genotypes
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topic_title	Rare variant association analysis in case-parents studies by allowing for missing parental genotypes Rare-variant association analysis (dpeaa)DE-He213 Case-parent trios (dpeaa)DE-He213 Collapsing method (dpeaa)DE-He213
topic	misc Rare-variant association analysis misc Case-parent trios misc Collapsing method
topic_unstemmed	misc Rare-variant association analysis misc Case-parent trios misc Collapsing method
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title	Rare variant association analysis in case-parents studies by allowing for missing parental genotypes
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title_full	Rare variant association analysis in case-parents studies by allowing for missing parental genotypes
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title_sort	rare variant association analysis in case-parents studies by allowing for missing parental genotypes
title_auth	Rare variant association analysis in case-parents studies by allowing for missing parental genotypes
abstract	Background The development of next-generation sequencing technologies has facilitated the identification of rare variants. Family-based design is commonly used to effectively control for population admixture and substructure, which is more prominent for rare variants. Case-parents studies, as typical strategies in family-based design, are widely used in rare variant-disease association analysis. Current methods in case-parents studies are based on complete case-parents data; however, parental genotypes may be missing in case-parents trios, and removing these data may lead to a loss in statistical power. The present study focuses on testing for rare variant-disease association in case-parents study by allowing for missing parental genotypes. Results In this report, we extended the collapsing method for rare variant association analysis in case-parents studies to allow for missing parental genotypes, and investigated the performance of two methods by using the difference of genotypes between affected offspring and their corresponding “complements” in case-parent trios and TDT framework. Using simulations, we showed that, compared with the methods just only using complete case-parents data, the proposed strategy allowing for missing parental genotypes, or even adding unrelated affected individuals, can greatly improve the statistical power and meanwhile is not affected by population stratification. Conclusions We conclude that adding case-parents data with missing parental genotypes to complete case-parents data set can greatly improve the power of our strategy for rare variant-disease association. © The Author(s). 2018
abstractGer	Background The development of next-generation sequencing technologies has facilitated the identification of rare variants. Family-based design is commonly used to effectively control for population admixture and substructure, which is more prominent for rare variants. Case-parents studies, as typical strategies in family-based design, are widely used in rare variant-disease association analysis. Current methods in case-parents studies are based on complete case-parents data; however, parental genotypes may be missing in case-parents trios, and removing these data may lead to a loss in statistical power. The present study focuses on testing for rare variant-disease association in case-parents study by allowing for missing parental genotypes. Results In this report, we extended the collapsing method for rare variant association analysis in case-parents studies to allow for missing parental genotypes, and investigated the performance of two methods by using the difference of genotypes between affected offspring and their corresponding “complements” in case-parent trios and TDT framework. Using simulations, we showed that, compared with the methods just only using complete case-parents data, the proposed strategy allowing for missing parental genotypes, or even adding unrelated affected individuals, can greatly improve the statistical power and meanwhile is not affected by population stratification. Conclusions We conclude that adding case-parents data with missing parental genotypes to complete case-parents data set can greatly improve the power of our strategy for rare variant-disease association. © The Author(s). 2018
abstract_unstemmed	Background The development of next-generation sequencing technologies has facilitated the identification of rare variants. Family-based design is commonly used to effectively control for population admixture and substructure, which is more prominent for rare variants. Case-parents studies, as typical strategies in family-based design, are widely used in rare variant-disease association analysis. Current methods in case-parents studies are based on complete case-parents data; however, parental genotypes may be missing in case-parents trios, and removing these data may lead to a loss in statistical power. The present study focuses on testing for rare variant-disease association in case-parents study by allowing for missing parental genotypes. Results In this report, we extended the collapsing method for rare variant association analysis in case-parents studies to allow for missing parental genotypes, and investigated the performance of two methods by using the difference of genotypes between affected offspring and their corresponding “complements” in case-parent trios and TDT framework. Using simulations, we showed that, compared with the methods just only using complete case-parents data, the proposed strategy allowing for missing parental genotypes, or even adding unrelated affected individuals, can greatly improve the statistical power and meanwhile is not affected by population stratification. Conclusions We conclude that adding case-parents data with missing parental genotypes to complete case-parents data set can greatly improve the power of our strategy for rare variant-disease association. © The Author(s). 2018
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title_short	Rare variant association analysis in case-parents studies by allowing for missing parental genotypes
url	https://dx.doi.org/10.1186/s12863-018-0597-8
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Family-based design is commonly used to effectively control for population admixture and substructure, which is more prominent for rare variants. Case-parents studies, as typical strategies in family-based design, are widely used in rare variant-disease association analysis. Current methods in case-parents studies are based on complete case-parents data; however, parental genotypes may be missing in case-parents trios, and removing these data may lead to a loss in statistical power. The present study focuses on testing for rare variant-disease association in case-parents study by allowing for missing parental genotypes. Results In this report, we extended the collapsing method for rare variant association analysis in case-parents studies to allow for missing parental genotypes, and investigated the performance of two methods by using the difference of genotypes between affected offspring and their corresponding “complements” in case-parent trios and TDT framework. Using simulations, we showed that, compared with the methods just only using complete case-parents data, the proposed strategy allowing for missing parental genotypes, or even adding unrelated affected individuals, can greatly improve the statistical power and meanwhile is not affected by population stratification. Conclusions We conclude that adding case-parents data with missing parental genotypes to complete case-parents data set can greatly improve the power of our strategy for rare variant-disease association.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Rare-variant association analysis</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Case-parent trios</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Collapsing method</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Xiang, Yang</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Xu, Chao</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Shen, Hui</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Deng, Hongwen</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">BMC genetics</subfield><subfield code="d">London : BioMed Central, 2000</subfield><subfield code="g">19(2018), 1 vom: 15. 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Rare variant association analysis in case-parents studies by allowing for missing parental genotypes

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