Welcome to CropGBM！
Crop Genomic Breeding machine (CropGBM) is a multifunctional Python3 program that integrates data preprocessing, population structure analysis, SNP selection, phenotype prediction, and data visualization.It has the following advantages:
- Use LightGBM algorithm to quickly and accurately predict phenotype values and support GPU-accelerated training.
- Supports selection and visualization of SNPs that are strongly related to phenotype.
- Support PCA and t-SNE two dimensionality reduction algorithms to extract SNP information.
- Support Kmeans and OPTICS two clustering algorithms to analyze the sample population structure.
- Plot histograms of heterozygosity rate, deletion rate, and frequency of alleles for genotype data.
Chinese version documentation: https://ibreeding-ch.github.io
Download link: https://github.com/YuetongXU/CropGBM
Cite: Jun Yan, Yuetong Xu, Qian Cheng, Shuqin Jiang, Qian Wang, Yingjie Xiao, Chuang Ma, Jianbing Yan and Xiangfeng Wang. LightGBM: accelerated genomically-designed crop breeding through ensemble learning.
Supplementary Information: Support data and materials for the manuscript is available at https://github.com/YuetongXU/Cropgbm-Paper
Contact us: email@example.com
Note: Academic users can download directly, industrial users first contact us.