刘小磊
博士生导师
硕士生导师
教师姓名：刘小磊
教师拼音名称：liuxiaolei
职称：教授
学历：博士研究生毕业
学位：博士
办公地点：第四综合楼G311
电子邮箱：
毕业院校：华中农业大学
所属院系：动物科学技术学院、动物医学院
所在单位：动物科学技术学院、动物医学院
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论文成果
- 10. Liu XL, Yang SB, Max FR, Zhang ZW, Fan B. Genome-wide association study of total number born and number born alive in pigs using both compressed mixed linear model and Bayes model[J] HEREDITAS, 2012,V34(10): 1261-1270..
- 9. Li M, Liu XL, Bradbury P, Yu J, Zhang YM, Todhunter RJ, et al. Enrichment of statistical power for genome-wide association studies. BMC Biol. 2014; 12: 73. doi:10.1186/s12915-014-0073-5..
- 8. Yin LL, Ma YL, Tao X, Zhu MJ, Yu M, Li XY, Liu XL*, Zhao SH*, The Progress and Prospect of Genomic Selection Models. ACTA VETERINARIA ET ZOOTECHNICA SINICA, 2019, 50(2): 233-242. (written in Chinese)..
- 7. Tang Y#, Liu XL#, Wang JB, Li M, Wang QS, Tian F, Su ZB, Pan YC, Liu D, Lipka AE, Buckler ES, Zhang Z. GAPIT Version 2: Enhanced Integrated Tool for Genomic Association and Prediction. Plant Gen. 2016, doi:10.3835/plantgenome2015.11.0120..
- 6. Zhang HH, Yin LL, Wang MY, Yuan XH, Liu XL. Factors affecting the accuracy of genomic selection for agricultural economic traits in maize, cattle, and pig populations. Front. Genet. doi: 10.3389/fgene.2019.00189..
- 5. Tang ZS, Fu YH, Xu JY, Zhu MJ, Li XY, Yu M, Zhao SH, Liu XL. Discovery of selection‐driven genetic differences of Duroc, Landrace, and Yorkshire pig breeds by EigenGWAS and Fst analyses. Animal Genetics. May 2020. DOI: 10.1111/age.12946..
- 4. Fu YH, Wang L, Tang ZS, Yin D, Xu JY, Fan Yu, Li XY, Zhao SH, Liu XL. An integration analysis based on genomic, transcriptomic and QTX information reveals credible candidate genes for fat-related traits in pigs. Animal Genetics. June 2020. DOI: 10.1111/age.12971.
- 3. Tang Y, Liu XL. G2P: A Genome-Wide-Association-Study Simulation Tool for Genotype Simulation, Phenotype Simulation, and Power Evaluation. Bioinformatics. btz126, https://doi.org/10.1093/bioinformatics/btz126..
- 2. Liu XL, Huang M, Fan B, Buckler ES, Zhang ZW. Iterative Usage of Fixed and Random Effect Models for Powerful and Efficient Genome-wide Association Studies. PLoS Genet. 2016:12(2):e1005767, doi:10.1371/journal.pgen.1005767..
- 1. Yin LL, Zhang HH, Zhou X, Yuan XH, Zhao SH, Li XY, Liu XL. KAML: improving genomic prediction accuracy of complex traits using machine learning determined parameters. Genome Biol 21, 146 (2020). https://doi.org/10.1186/s13059-020-02052-w..
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