|Iterative usage of fixed and random effect models for powerful and efficient genome-wide association studies|
X Liu, M Huang, B Fan, ES Buckler, Z Zhang
PLoS genetics 12 (2), e1005767, 2016
|GAPIT version 2: an enhanced integrated tool for genomic association and prediction|
Y Tang, X Liu, J Wang, M Li, Q Wang, F Tian, Z Su, Y Pan, D Liu, AE Lipka, ...
The plant genome 9 (2), 1-9, 2016
|Identification of genetic variants associated with maize flowering time using an extremely large multi‐genetic background population|
Y Li, C Li, PJ Bradbury, X Liu, F Lu, CM Romay, JC Glaubitz, X Wu, ...
The Plant Journal 86 (5), 391-402, 2016
|Enrichment of statistical power for genome-wide association studies|
M Li, X Liu, P Bradbury, J Yu, YM Zhang, RJ Todhunter, ES Buckler, ...
BMC biology 12 (1), 1-10, 2014
|Genetic determinants of pig birth weight variability|
X Wang, X Liu, D Deng, M Yu, X Li
BMC genetics 17 (S1), S15, 2016
|BLINK: a package for the next level of genome-wide association studies with both individuals and markers in the millions|
M Huang, X Liu, Y Zhou, RM Summers, Z Zhang
GigaScience 8 (2), giy154, 2019
|Factors affecting the accuracy of genomic selection for agricultural economic traits in maize, cattle, and pig populations|
H Zhang, L Yin, M Wang, X Yuan, X Liu
Frontiers in genetics 10, 189, 2019
|Stepwise selection on homeologous PRR genes controlling flowering and maturity during soybean domestication|
S Lu, L Dong, C Fang, S Liu, L Kong, Q Cheng, L Chen, T Su, H Nan, ...
Nature Genetics 52 (4), 428-436, 2020
|Genome-Wide Association Study Reveals Candidate Genes for Growth Relevant Traits in Pigs|
Z Tang, J Xu, L Yin, D Yin, M Zhu, M Yu, X Li, S Zhao, X Liu
Frontiers in genetics 10, 302, 2019
|Genome-wide association study of the backfat thickness trait in two pig populations|
D ZHU, X LIU, R MAX, Z ZHANG, S ZHAO, B FAN
Frontiers of Agricultural Science and Engineering 1 (2), 91-95, 2014
|G2P: a Genome-Wide-Association-Study simulation tool for genotype simulation, phenotype simulation and power evaluation|
Y Tang, X Liu
Bioinformatics 35 (19), 3852-3854, 2019
|rMVP: A Memory-efficient, Visualization-enhanced, and Parallel-accelerated tool for Genome-Wide Association Study|
L Yin, H Zhang, Z Tang, J Xu, D Yin, Z Zhang, X Yuan, M Zhu, S Zhao, X Li, ...
|KAML: improving genomic prediction accuracy of complex traits using machine learning determined parameters|
L Yin, H Zhang, X Zhou, X Yuan, S Zhao, X Li, X Liu
Genome biology 21 (1), 1-22, 2020
|An integration analysis based on genomic, transcriptomic and QTX information reveals credible candidate genes for fat‐related traits in pigs|
Y Fu, L Wang, Z Tang, D Yin, J Xu, Y Fan, X Li, S Zhao, X Liu
Animal Genetics 51 (5), 683-693, 2020
|A gene prioritization method based on a swine multi-omics knowledgebase and a deep learning model|
Y Fu, J Xu, Z Tang, L Wang, D Yin, Y Fan, D Zhang, F Deng, Y Zhang, ...
Communications Biology 3 (1), 1-11, 2020
|Discovery of selection‐driven genetic differences of Duroc, Landrace, and Yorkshire pig breeds by EigenGWAS and Fst analyses|
Z Tang, Y Fu, J Xu, M Zhu, X Li, M Yu, S Zhao, X Liu
Animal Genetics, 2020