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Modeling Multiple Responses via Bootstrapping Margins with an Application to Genetic Association Testing.

Statistics and its interface

Zhao J, Zhang H.
PMID: 26543519
Stat Interface. 2016;9(1):47-56. doi: 10.4310/SII.2016.v9.n1.a5.

The need for analysis of multiple responses arises from many applications. In behavioral science, for example, comorbidity is a common phenomenon where multiple disorders occur in the same person. The advantage of jointly analyzing multiple correlated responses has been...

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Zhao J, Zhang H. Modeling Multiple Responses via Bootstrapping Margins with an Application to Genetic Association Testing. Stat Interface. 2016;9(1):47-56doi: 10.4310/SII.2016.v9.n1.a5.
Zhao, J., & Zhang, H. (2016). Modeling Multiple Responses via Bootstrapping Margins with an Application to Genetic Association Testing. Statistics and its interface, 9(1), 47-56. https://doi.org/10.4310/SII.2016.v9.n1.a5
Zhao, Jiwei, and Zhang, Heping. "Modeling Multiple Responses via Bootstrapping Margins with an Application to Genetic Association Testing." Statistics and its interface vol. 9,1 (2016): 47-56. doi: https://doi.org/10.4310/SII.2016.v9.n1.a5
Zhao J, Zhang H. Modeling Multiple Responses via Bootstrapping Margins with an Application to Genetic Association Testing. Stat Interface. 2016;9(1):47-56. doi: 10.4310/SII.2016.v9.n1.a5. PMID: 26543519; PMCID: PMC4629876.
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Gene-based and pathway-based genome-wide association study of alcohol dependence.

Shanghai archives of psychiatry

Zuo L, Zhang CK, Sayward FG, Cheung KH, Wang K, Krystal JH, Zhao H, Luo X.
PMID: 26120261
Shanghai Arch Psychiatry. 2015 Apr 25;27(2):111-8. doi: 10.11919/j.issn.1002-0829.215031.

BACKGROUND: The organization of risk genes within signaling pathways may provide clues about the converging neurobiological effects of risk genes for alcohol dependence.AIM: Identify risk genes and risk gene pathways for alcohol dependence.METHODS: We conducted a pathway-based genome-wide association...

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Zuo L, Zhang CK, Sayward FG, et al. Gene-based and pathway-based genome-wide association study of alcohol dependence. Shanghai Arch Psychiatry. 2015;27(2):111-8doi: 10.11919/j.issn.1002-0829.215031.
Zuo, L., Zhang, C. K., Sayward, F. G., Cheung, K. H., Wang, K., Krystal, J. H., Zhao, H., & Luo, X. (2015). Gene-based and pathway-based genome-wide association study of alcohol dependence. Shanghai archives of psychiatry, 27(2), 111-8. https://doi.org/10.11919/j.issn.1002-0829.215031
Zuo, Lingjun, et al. "Gene-based and pathway-based genome-wide association study of alcohol dependence." Shanghai archives of psychiatry vol. 27,2 (2015): 111-8. doi: https://doi.org/10.11919/j.issn.1002-0829.215031
Zuo L, Zhang CK, Sayward FG, Cheung KH, Wang K, Krystal JH, Zhao H, Luo X. Gene-based and pathway-based genome-wide association study of alcohol dependence. Shanghai Arch Psychiatry. 2015 Apr 25;27(2):111-8. doi: 10.11919/j.issn.1002-0829.215031. PMID: 26120261; PMCID: PMC4466852.
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Evaluating methods for modeling epistasis networks with application to head and neck cancer.

Cancer informatics

Talluri R, Shete S.
PMID: 25733798
Cancer Inform. 2015 Feb 10;14:17-23. doi: 10.4137/CIN.S17289. eCollection 2015.

Epistasis helps to explain how multiple single-nucleotide polymorphisms (SNPs) interact to cause disease. A variety of tools have been developed to detect epistasis. In this article, we explore the strengths and weaknesses of an information theory approach for detecting...

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Talluri R, Shete S. Evaluating methods for modeling epistasis networks with application to head and neck cancer. Cancer Inform. 2015;14:17-23doi: 10.4137/CIN.S17289.
Talluri, R., & Shete, S. (2015). Evaluating methods for modeling epistasis networks with application to head and neck cancer. Cancer informatics, 1417-23. https://doi.org/10.4137/CIN.S17289
Talluri, Rajesh, and Shete, Sanjay. "Evaluating methods for modeling epistasis networks with application to head and neck cancer." Cancer informatics vol. 14 (2015): 17-23. doi: https://doi.org/10.4137/CIN.S17289
Talluri R, Shete S. Evaluating methods for modeling epistasis networks with application to head and neck cancer. Cancer Inform. 2015 Feb 10;14:17-23. doi: 10.4137/CIN.S17289. eCollection 2015. PMID: 25733798; PMCID: PMC4332043.
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THE SCREENING AND RANKING ALGORITHM FOR CHANGE-POINTS DETECTION IN MULTIPLE SAMPLES.

The annals of applied statistics

Song C, Min X, Zhang H.
PMID: 28090239
Ann Appl Stat. 2016 Dec;10(4):2102-2129. doi: 10.1214/16-AOAS966. Epub 2017 Jan 05.

The chromosome copy number variation (CNV) is the deviation of genomic regions from their normal copy number states, which may associate with many human diseases. Current genetic studies usually collect hundreds to thousands of samples to study the association...

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Song C, Min X, Zhang H. THE SCREENING AND RANKING ALGORITHM FOR CHANGE-POINTS DETECTION IN MULTIPLE SAMPLES. Ann Appl Stat. 2017;10(4):2102-2129doi: 10.1214/16-AOAS966.
Song, C., Min, X., & Zhang, H. (2016). THE SCREENING AND RANKING ALGORITHM FOR CHANGE-POINTS DETECTION IN MULTIPLE SAMPLES. The annals of applied statistics, 10(4), 2102-2129. https://doi.org/10.1214/16-AOAS966
Song, Chi, et al. "THE SCREENING AND RANKING ALGORITHM FOR CHANGE-POINTS DETECTION IN MULTIPLE SAMPLES." The annals of applied statistics vol. 10,4 (2016): 2102-2129. doi: https://doi.org/10.1214/16-AOAS966
Song C, Min X, Zhang H. THE SCREENING AND RANKING ALGORITHM FOR CHANGE-POINTS DETECTION IN MULTIPLE SAMPLES. Ann Appl Stat. 2016 Dec;10(4):2102-2129. doi: 10.1214/16-AOAS966. Epub 2017 Jan 05. PMID: 28090239; PMCID: PMC5233178.
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Assessing the Association of Mitochondrial Genetic Variation With Primary Open-Angle Glaucoma Using Gene-Set Analyses.

Investigative ophthalmology & visual science

Khawaja AP, Cooke Bailey JN, Kang JH, Allingham RR, Hauser MA, Brilliant M, Budenz DL, Christen WG, Fingert J, Gaasterland D, Gaasterland T, Kraft P, Lee RK, Lichter PR, Liu Y, Medeiros F, Moroi SE, Richards JE, Realini T, Ritch R, Schuman JS, Scott WK, Singh K, Sit AJ, Vollrath D, Wollstein G, Zack DJ, Zhang K, Pericak-Vance M, Weinreb RN, Haines JL, Pasquale LR, Wiggs JL.
PMID: 27661856
Invest Ophthalmol Vis Sci. 2016 Sep 01;57(11):5046-5052. doi: 10.1167/iovs.16-20017.

PURPOSE: Recent studies indicate that mitochondrial proteins may contribute to the pathogenesis of primary open-angle glaucoma (POAG). In this study, we examined the association between POAG and common variations in gene-encoding mitochondrial proteins.METHODS: We examined genetic data from 3430...

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Khawaja AP, Cooke Bailey JN, Kang JH, et al. Assessing the Association of Mitochondrial Genetic Variation With Primary Open-Angle Glaucoma Using Gene-Set Analyses. Invest Ophthalmol Vis Sci. 2016;57(11):5046-5052doi: 10.1167/iovs.16-20017.
Khawaja, A. P., Cooke Bailey, J. N., Kang, J. H., Allingham, R. R., Hauser, M. A., Brilliant, M., Budenz, D. L., Christen, W. G., Fingert, J., Gaasterland, D., Gaasterland, T., Kraft, P., Lee, R. K., Lichter, P. R., Liu, Y., Medeiros, F., Moroi, S. E., Richards, J. E., Realini, T., Ritch, R., Schuman, J. S., Scott, W. K., Singh, K., Sit, A. J., Vollrath, D., Wollstein, G., Zack, D. J., Zhang, K., Pericak-Vance, M., Weinreb, R. N., Haines, J. L., Pasquale, L. R., & Wiggs, J. L. (2016). Assessing the Association of Mitochondrial Genetic Variation With Primary Open-Angle Glaucoma Using Gene-Set Analyses. Investigative ophthalmology & visual science, 57(11), 5046-5052. https://doi.org/10.1167/iovs.16-20017
Khawaja, Anthony P, et al. "Assessing the Association of Mitochondrial Genetic Variation With Primary Open-Angle Glaucoma Using Gene-Set Analyses." Investigative ophthalmology & visual science vol. 57,11 (2016): 5046-5052. doi: https://doi.org/10.1167/iovs.16-20017
Khawaja AP, Cooke Bailey JN, Kang JH, Allingham RR, Hauser MA, Brilliant M, Budenz DL, Christen WG, Fingert J, Gaasterland D, Gaasterland T, Kraft P, Lee RK, Lichter PR, Liu Y, Medeiros F, Moroi SE, Richards JE, Realini T, Ritch R, Schuman JS, Scott WK, Singh K, Sit AJ, Vollrath D, Wollstein G, Zack DJ, Zhang K, Pericak-Vance M, Weinreb RN, Haines JL, Pasquale LR, Wiggs JL. Assessing the Association of Mitochondrial Genetic Variation With Primary Open-Angle Glaucoma Using Gene-Set Analyses. Invest Ophthalmol Vis Sci. 2016 Sep 01;57(11):5046-5052. doi: 10.1167/iovs.16-20017. PMID: 27661856; PMCID: PMC5040191.
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Meta-analysis of Genome-Wide Association Studies for Extraversion: Findings from the Genetics of Personality Consortium.

Behavior genetics

van den Berg SM, de Moor MH, Verweij KJ, Krueger RF, Luciano M, Arias Vasquez A, Matteson LK, Derringer J, Esko T, Amin N, Gordon SD, Hansell NK, Hart AB, Seppälä I, Huffman JE, Konte B, Lahti J, Lee M, Miller M, Nutile T, Tanaka T, Teumer A, Viktorin A, Wedenoja J, Abdellaoui A, Abecasis GR, Adkins DE, Agrawal A, Allik J, Appel K, Bigdeli TB, Busonero F, Campbell H, Costa PT, Smith GD, Davies G, de Wit H, Ding J, Engelhardt BE, Eriksson JG, Fedko IO, Ferrucci L, Franke B, Giegling I, Grucza R, Hartmann AM, Heath AC, Heinonen K, Henders AK, Homuth G, Hottenga JJ, Iacono WG, Janzing J, Jokela M, Karlsson R, Kemp JP, Kirkpatrick MG, Latvala A, Lehtimäki T, Liewald DC, Madden PA, Magri C, Magnusson PK, Marten J, Maschio A, Mbarek H, Medland SE, Mihailov E, Milaneschi Y, Montgomery GW, Nauck M, Nivard MG, Ouwens KG, Palotie A, Pettersson E, Polasek O, Qian Y, Pulkki-Råback L, Raitakari OT, Realo A, Rose RJ, Ruggiero D, Schmidt CO, Slutske WS, Sorice R, Starr JM, St Pourcain B, Sutin AR, Timpson NJ, Trochet H, Vermeulen S, Vuoksimaa E, Widen E, Wouda J, Wright MJ, Zgaga L, Porteous D, Minelli A, Palmer AA, Rujescu D, Ciullo M, Hayward C, Rudan I, Metspalu A, Kaprio J, Deary IJ, Räikkönen K, Wilson JF, Keltikangas-Järvinen L, Bierut LJ, Hettema JM, Grabe HJ, Penninx BW, van Duijn CM, Evans DM, Schlessinger D, Pedersen NL, Terracciano A, McGue M, Martin NG, Boomsma DI.
PMID: 26362575
Behav Genet. 2016 Mar;46(2):170-82. doi: 10.1007/s10519-015-9735-5. Epub 2015 Sep 11.

Extraversion is a relatively stable and heritable personality trait associated with numerous psychosocial, lifestyle and health outcomes. Despite its substantial heritability, no genetic variants have been detected in previous genome-wide association (GWA) studies, which may be due to relatively...

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van den Berg SM, de Moor MH, Verweij KJ, et al. Meta-analysis of Genome-Wide Association Studies for Extraversion: Findings from the Genetics of Personality Consortium. Behav Genet. 2015;46(2):170-82doi: 10.1007/s10519-015-9735-5.
van den Berg, S. M., de Moor, M. H., Verweij, K. J., Krueger, R. F., Luciano, M., Arias Vasquez, A., Matteson, L. K., Derringer, J., Esko, T., Amin, N., Gordon, S. D., Hansell, N. K., Hart, A. B., Seppälä, I., Huffman, J. E., Konte, B., Lahti, J., Lee, M., Miller, M., Nutile, T., Tanaka, T., Teumer, A., Viktorin, A., Wedenoja, J., Abdellaoui, A., Abecasis, G. R., Adkins, D. E., Agrawal, A., Allik, J., Appel, K., Bigdeli, T. B., Busonero, F., Campbell, H., Costa, P. T., Smith, G. D., Davies, G., de Wit, H., Ding, J., Engelhardt, B. E., Eriksson, J. G., Fedko, I. O., Ferrucci, L., Franke, B., Giegling, I., Grucza, R., Hartmann, A. M., Heath, A. C., Heinonen, K., Henders, A. K., Homuth, G., Hottenga, J. J., Iacono, W. G., Janzing, J., Jokela, M., Karlsson, R., Kemp, J. P., Kirkpatrick, M. G., Latvala, A., Lehtimäki, T., Liewald, D. C., Madden, P. A., Magri, C., Magnusson, P. K., Marten, J., Maschio, A., Mbarek, H., Medland, S. E., Mihailov, E., Milaneschi, Y., Montgomery, G. W., Nauck, M., Nivard, M. G., Ouwens, K. G., Palotie, A., Pettersson, E., Polasek, O., Qian, Y., Pulkki-Råback, L., Raitakari, O. T., Realo, A., Rose, R. J., Ruggiero, D., Schmidt, C. O., Slutske, W. S., Sorice, R., Starr, J. M., St Pourcain, B., Sutin, A. R., Timpson, N. J., Trochet, H., Vermeulen, S., Vuoksimaa, E., Widen, E., Wouda, J., Wright, M. J., Zgaga, L., Porteous, D., Minelli, A., Palmer, A. A., Rujescu, D., Ciullo, M., Hayward, C., Rudan, I., Metspalu, A., Kaprio, J., Deary, I. J., Räikkönen, K., Wilson, J. F., Keltikangas-Järvinen, L., Bierut, L. J., Hettema, J. M., Grabe, H. J., Penninx, B. W., van Duijn, C. M., Evans, D. M., Schlessinger, D., Pedersen, N. L., Terracciano, A., McGue, M., Martin, N. G., & Boomsma, D. I. (2016). Meta-analysis of Genome-Wide Association Studies for Extraversion: Findings from the Genetics of Personality Consortium. Behavior genetics, 46(2), 170-82. https://doi.org/10.1007/s10519-015-9735-5
van den Berg, Stéphanie M, et al. "Meta-analysis of Genome-Wide Association Studies for Extraversion: Findings from the Genetics of Personality Consortium." Behavior genetics vol. 46,2 (2016): 170-82. doi: https://doi.org/10.1007/s10519-015-9735-5
van den Berg SM, de Moor MH, Verweij KJ, Krueger RF, Luciano M, Arias Vasquez A, Matteson LK, Derringer J, Esko T, Amin N, Gordon SD, Hansell NK, Hart AB, Seppälä I, Huffman JE, Konte B, Lahti J, Lee M, Miller M, Nutile T, Tanaka T, Teumer A, Viktorin A, Wedenoja J, Abdellaoui A, Abecasis GR, Adkins DE, Agrawal A, Allik J, Appel K, Bigdeli TB, Busonero F, Campbell H, Costa PT, Smith GD, Davies G, de Wit H, Ding J, Engelhardt BE, Eriksson JG, Fedko IO, Ferrucci L, Franke B, Giegling I, Grucza R, Hartmann AM, Heath AC, Heinonen K, Henders AK, Homuth G, Hottenga JJ, Iacono WG, Janzing J, Jokela M, Karlsson R, Kemp JP, Kirkpatrick MG, Latvala A, Lehtimäki T, Liewald DC, Madden PA, Magri C, Magnusson PK, Marten J, Maschio A, Mbarek H, Medland SE, Mihailov E, Milaneschi Y, Montgomery GW, Nauck M, Nivard MG, Ouwens KG, Palotie A, Pettersson E, Polasek O, Qian Y, Pulkki-Råback L, Raitakari OT, Realo A, Rose RJ, Ruggiero D, Schmidt CO, Slutske WS, Sorice R, Starr JM, St Pourcain B, Sutin AR, Timpson NJ, Trochet H, Vermeulen S, Vuoksimaa E, Widen E, Wouda J, Wright MJ, Zgaga L, Porteous D, Minelli A, Palmer AA, Rujescu D, Ciullo M, Hayward C, Rudan I, Metspalu A, Kaprio J, Deary IJ, Räikkönen K, Wilson JF, Keltikangas-Järvinen L, Bierut LJ, Hettema JM, Grabe HJ, Penninx BW, van Duijn CM, Evans DM, Schlessinger D, Pedersen NL, Terracciano A, McGue M, Martin NG, Boomsma DI. Meta-analysis of Genome-Wide Association Studies for Extraversion: Findings from the Genetics of Personality Consortium. Behav Genet. 2016 Mar;46(2):170-82. doi: 10.1007/s10519-015-9735-5. Epub 2015 Sep 11. PMID: 26362575; PMCID: PMC4751159.
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Modeling Hybrid Traits for Comorbidity and Genetic Studies of Alcohol and Nicotine Co-Dependence.

The annals of applied statistics

Zhang H, Liu D, Zhao J, Bi X.
PMID: 30666272
Ann Appl Stat. 2018 Dec;12(4):2359-2378. doi: 10.1214/18-AOAS1156. Epub 2018 Nov 13.

We propose a novel multivariate model for analyzing hybrid traits and identifying genetic factors for comorbid conditions. Comorbidity is a common phenomenon in mental health in which an individual suffers from multiple disorders simultaneously. For example, in the Study...

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Zhang H, Liu D, Zhao J, et al. Modeling Hybrid Traits for Comorbidity and Genetic Studies of Alcohol and Nicotine Co-Dependence. Ann Appl Stat. 2018;12(4):2359-2378doi: 10.1214/18-AOAS1156.
Zhang, H., Liu, D., Zhao, J., & Bi, X. (2018). Modeling Hybrid Traits for Comorbidity and Genetic Studies of Alcohol and Nicotine Co-Dependence. The annals of applied statistics, 12(4), 2359-2378. https://doi.org/10.1214/18-AOAS1156
Zhang, Heping, et al. "Modeling Hybrid Traits for Comorbidity and Genetic Studies of Alcohol and Nicotine Co-Dependence." The annals of applied statistics vol. 12,4 (2018): 2359-2378. doi: https://doi.org/10.1214/18-AOAS1156
Zhang H, Liu D, Zhao J, Bi X. Modeling Hybrid Traits for Comorbidity and Genetic Studies of Alcohol and Nicotine Co-Dependence. Ann Appl Stat. 2018 Dec;12(4):2359-2378. doi: 10.1214/18-AOAS1156. Epub 2018 Nov 13. PMID: 30666272; PMCID: PMC6338437.
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Selection of X-chromosome Inactivation Model.

Cancer informatics

Wang J, Talluri R, Shete S.
PMID: 29308008
Cancer Inform. 2017 Dec 17;16:1176935117747272. doi: 10.1177/1176935117747272. eCollection 2017.

To address the complexity of the X-chromosome inactivation (XCI) process, we previously developed a unified approach for the association test for X-chromosomal single-nucleotide polymorphisms (SNPs) and the disease of interest, accounting for different biological possibilities of XCI: random, skewed,...

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Wang J, Talluri R, Shete S. Selection of X-chromosome Inactivation Model. Cancer Inform. 2017;16:1176935117747272doi: 10.1177/1176935117747272.
Wang, J., Talluri, R., & Shete, S. (2017). Selection of X-chromosome Inactivation Model. Cancer informatics, 161176935117747272. https://doi.org/10.1177/1176935117747272
Wang, Jian, et al. "Selection of X-chromosome Inactivation Model." Cancer informatics vol. 16 (2017): 1176935117747272. doi: https://doi.org/10.1177/1176935117747272
Wang J, Talluri R, Shete S. Selection of X-chromosome Inactivation Model. Cancer Inform. 2017 Dec 17;16:1176935117747272. doi: 10.1177/1176935117747272. eCollection 2017. PMID: 29308008; PMCID: PMC5751921.
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Nonsyndromic cleft lip with or without cleft palate and cancer: Evaluation of a possible common genetic background through the analysis of GWAS data.

Genomics data

Dunkhase E, Ludwig KU, Knapp M, Skibola CF, Figueiredo JC, Hosking FJ, Ellinghaus E, Landi MT, Ma H, Nakagawa H, Kim JW, Han J, Yang P, Böhmer AC, Mattheisen M, Nöthen MM, Mangold E.
PMID: 27630819
Genom Data. 2016 Aug 26;10:22-9. doi: 10.1016/j.gdata.2016.08.017. eCollection 2016 Dec.

Previous research suggests a genetic overlap between nonsyndromic cleft lip with or without cleft palate (NSCL/P) and cancer. The aim of the present study was to identify common genetic risk loci for NSCL/P and cancer entities that have been...

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Dunkhase E, Ludwig KU, Knapp M, et al. Nonsyndromic cleft lip with or without cleft palate and cancer: Evaluation of a possible common genetic background through the analysis of GWAS data. Genom Data. 2016;10:22-9doi: 10.1016/j.gdata.2016.08.017.
Dunkhase, E., Ludwig, K. U., Knapp, M., Skibola, C. F., Figueiredo, J. C., Hosking, F. J., Ellinghaus, E., Landi, M. T., Ma, H., Nakagawa, H., Kim, J. W., Han, J., Yang, P., Böhmer, A. C., Mattheisen, M., Nöthen, M. M., & Mangold, E. (2016). Nonsyndromic cleft lip with or without cleft palate and cancer: Evaluation of a possible common genetic background through the analysis of GWAS data. Genomics data, 1022-9. https://doi.org/10.1016/j.gdata.2016.08.017
Dunkhase, Eva, et al. "Nonsyndromic cleft lip with or without cleft palate and cancer: Evaluation of a possible common genetic background through the analysis of GWAS data." Genomics data vol. 10 (2016): 22-9. doi: https://doi.org/10.1016/j.gdata.2016.08.017
Dunkhase E, Ludwig KU, Knapp M, Skibola CF, Figueiredo JC, Hosking FJ, Ellinghaus E, Landi MT, Ma H, Nakagawa H, Kim JW, Han J, Yang P, Böhmer AC, Mattheisen M, Nöthen MM, Mangold E. Nonsyndromic cleft lip with or without cleft palate and cancer: Evaluation of a possible common genetic background through the analysis of GWAS data. Genom Data. 2016 Aug 26;10:22-9. doi: 10.1016/j.gdata.2016.08.017. eCollection 2016 Dec. PMID: 27630819; PMCID: PMC5013250.
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Sex difference of autosomal alleles in populations of European and African descent.

Genes & genomics

Zuo L, Wang T, Lin X, Wang J, Tan Y, Wang X, Yu X, Luo X.
PMID: 26702338
Genes Genomics. 2015 Dec 01;37(12):1007-1016. doi: 10.1007/s13258-015-0332-z. Epub 2015 Sep 03.

In the present study, we aimed to report the individual sex-different genetic markers across autosomes in European- and African-origin populations. A total of 8,400 females and 8,081 males in 19 independent cohorts were genotyped across genomes using Illumina or...

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Zuo L, Wang T, Lin X, et al. Sex difference of autosomal alleles in populations of European and African descent. Genes Genomics. 2015;37(12):1007-1016doi: 10.1007/s13258-015-0332-z.
Zuo, L., Wang, T., Lin, X., Wang, J., Tan, Y., Wang, X., Yu, X., & Luo, X. (2015). Sex difference of autosomal alleles in populations of European and African descent. Genes & genomics, 37(12), 1007-1016. https://doi.org/10.1007/s13258-015-0332-z
Zuo, Lingjun, et al. "Sex difference of autosomal alleles in populations of European and African descent." Genes & genomics vol. 37,12 (2015): 1007-1016. doi: https://doi.org/10.1007/s13258-015-0332-z
Zuo L, Wang T, Lin X, Wang J, Tan Y, Wang X, Yu X, Luo X. Sex difference of autosomal alleles in populations of European and African descent. Genes Genomics. 2015 Dec 01;37(12):1007-1016. doi: 10.1007/s13258-015-0332-z. Epub 2015 Sep 03. PMID: 26702338; PMCID: PMC4684836.
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Family-Based Multi-SNP X Chromosome Analysis Using Parent Information.

Frontiers in genetics

Wise AS, Shi M, Weinberg CR.
PMID: 26941777
Front Genet. 2016 Feb 22;7:20. doi: 10.3389/fgene.2016.00020. eCollection 2016.

We propose a method for association analysis of haplotypes on the X chromosome that offers both improved power and robustness to population stratification in studies of affected offspring and their parents if all three have been genotyped. The method...

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Wise AS, Shi M, Weinberg CR. Family-Based Multi-SNP X Chromosome Analysis Using Parent Information. Front Genet. 2016;7:20doi: 10.3389/fgene.2016.00020.
Wise, A. S., Shi, M., & Weinberg, C. R. (2016). Family-Based Multi-SNP X Chromosome Analysis Using Parent Information. Frontiers in genetics, 720. https://doi.org/10.3389/fgene.2016.00020
Wise, Alison S, et al. "Family-Based Multi-SNP X Chromosome Analysis Using Parent Information." Frontiers in genetics vol. 7 (2016): 20. doi: https://doi.org/10.3389/fgene.2016.00020
Wise AS, Shi M, Weinberg CR. Family-Based Multi-SNP X Chromosome Analysis Using Parent Information. Front Genet. 2016 Feb 22;7:20. doi: 10.3389/fgene.2016.00020. eCollection 2016. PMID: 26941777; PMCID: PMC4761843.
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Genotype-Based Bayesian Analysis of Gene-Environment Interactions with Multiple Genetic Markers and Misclassification in Environmental Factors.

Journal of probability and statistics

Lobach I, Fan R.
PMID: 26180529
J Probab Stat. 2012;2012. doi: 10.1155/2012/151259.

A key component to understanding etiology of complex diseases, such as cancer, diabetes, alcohol dependence, is to investigate gene-environment interactions. This work is motivated by the following two concerns in the analysis of gene-environment interactions. First, multiple genetic markers...

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Lobach I, Fan R. Genotype-Based Bayesian Analysis of Gene-Environment Interactions with Multiple Genetic Markers and Misclassification in Environmental Factors. J Probab Stat. 2012;2012doi: 10.1155/2012/151259.
Lobach, I., & Fan, R. (2012). Genotype-Based Bayesian Analysis of Gene-Environment Interactions with Multiple Genetic Markers and Misclassification in Environmental Factors. Journal of probability and statistics, 2012. https://doi.org/10.1155/2012/151259
Lobach, Iryna, and Fan, Ruzong. "Genotype-Based Bayesian Analysis of Gene-Environment Interactions with Multiple Genetic Markers and Misclassification in Environmental Factors." Journal of probability and statistics vol. 2012 (2012). doi: https://doi.org/10.1155/2012/151259
Lobach I, Fan R. Genotype-Based Bayesian Analysis of Gene-Environment Interactions with Multiple Genetic Markers and Misclassification in Environmental Factors. J Probab Stat. 2012;2012. doi: 10.1155/2012/151259. PMID: 26180529; PMCID: PMC4500528.
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Showing 1 to 12 of 31 entries