Aquaculture Molecular Breeding Platform (AMBP) is a
portal for genetic data analysis in aquatic species of
farming interest. AMBP integrates pipelines for genotype
imputation, kinship deduction, population structure
inference, genome-wide association study (GWAS),
genomic selection (GS), and genomic mating (GM). It also
provides a public-domain archive for genetic variants
and haplotype reference panels of 18 aquaculture
Qifan Zeng+, Baojun Zhao+, Hao Wang+, Mengqiu Wang, Mingxuan Teng, Jingjie Hu, Zhenmin Bao, Yangfan Wang*. (2022) Aquaculture Molecular Breeding Platform (AMBP): a comprehensive web server for genotype imputation and genetic analysis in aquaculture. Nucleic Acids Research, gkac424, https://doi.org/10.1093/nar/gkac424.
● The Platform for High-Performance Computing and Systematic
Simulation at Qingdao National Laboratory for Marine Science
and Technology (QNLM) will undergo annual maintenance from 9
June 2022 to 13 June 2022. During this time, AMBP servers
may be intermittently unavailable. We are sorry for the
inconvenience. Please contact AMBP with concerns: AMBP_MGB@hotmail.com
2021 MOE Key Laboratory of Marine Genetics and Breeding,
of Marine Life Sciences, Ocean University of China
Road, Qingdao 266003, Shandong Province, China
Genotype imputation leverages local
linkage disequilibrium to infer missing genotypes of
target samples. In AMBP, users can carry out online
imputation for 18 aquaculture species by two imputation
Users can search SNPs by genomic coordinates and check
their predicted effects or functions.
Users can upload custom datasets to scan and identify simple structural variation (SV) and complex genomic rearrangements (CGR) by using ‘Starfish’ algorithm.
investigate the population structure of target samples
with genotype datasets. Genetic clustering is performed
by genetic ancestry estimation and principal component
infer pairwise relationships from estimated IBD segments
and kinship coefficients.
upload custom datasets and scan markers across the whole
genomes to locate genetic variations associated with a
upload custom datasets for Genomic Estimated Breeding
Values (GEBV) prediction. AMBP includes three GS models:
Genomic Best Linear Unbiased Prediction (GBLUP),
Bayesian Lasso, and Sparse Neural Networks (SNN).
(GM) represents an approach to maximize genetic gain
while constraining inbreeding within a targeted range.
Users can compare the genetic improvements made by GS
and GM across multiple simulated generations.
download the reference panel and the genome
assemblies of each species
for each module.
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