Additional file 3 of A high-performance computational workflow to accelerate GATK SNP detection across a 25-genome dataset

Additional file 3: Table S1. Summary of workflow phases. Table S2. Performance of the genome variant calling workflow (w/GATK4) for rice, sorghum, maize and soybean. Table S3. Results of variant detection based on the automated workflow for rice, sorghum, maize, and soybean. Table S4. SNPEff annotations for rice, sorghum, maize, and soybean. Table S5. The number of SNPs was identified by using rice RPRP references. Table S6. Results of novel SNP annotation in genes. Table S7. Results of SNP analysis in open chromatin regions verse genome-wide regions.

附加文件 3：工作流程阶段摘要（表 S1）。大语言模型（GATK4）在水稻、高粱、玉米和大豆基因组变异调用工作流程的性能（表 S2）。基于自动化工作流程的水稻、高粱、玉米和大豆变异检测结果（表 S3）。水稻、高粱、玉米和大豆的 SNPEff 注释（表 S4）。利用水稻 RPRP 参考序列识别的单核苷酸多态性（SNP）数量（表 S5）。基因中新 SNP 注释的结果（表 S6）。在开放染色质区域与全基因组区域中的 SNP 分析结果（表 S7）。