The data for the study "GS-Impute: a neural network framework for accurate imputation of low-density markers in across-population genomic selection"

The data for the study "GS-Impute: a neural network framework for accurate imputation of low-density markers in across-population genomic selection"Upon decompression, users will find:1. Rice and maize genotype datasets with systematic and sporadic missing patterns.2. Rice and maize genotype datasets before and after artificial missing simulation (named original_geno_file and unimputed genotype file respectively）3. Rice and maize genotype datasets with different missing rates (10%, 30% and 50%).4. Refined reference panels with redundant markers removed.Note: The original reference panels are available for download via the Plant-ImputeDB platform (https://gong_lab.hzau.edu.cn/Plant_imputeDB/#!/).