In Silico Sorghum GxExM Dataset For Prediction Algorithm Comparisons

# In Silico Sorghum GxExM Dataset For Prediction Algorithm Comparisons ## BackgroundA simulated Multi-Environment Trial (MET) dataset to stimulate the development and comparisons of predictive algorithms to deconvolute genotype-by-environment-by-management interactions in plant breeding. Contains Genomic (SNP & QTL) & Phenotypic Data for Multiple Traits. ### Data##### Mapmap.csvPositional Information on the Causal (Quantitative Trait Loci - QTL) and Non-Causal (Single Nucleotide Polymorphisms - SNP) Genomic Sites within and across chromosomesColumn 1: Chromosome NumberColumn 2: Marker IDColumn 3: Position (Morgans)##### Genotypeqtl_effects.csvInformation on Causal Genomic Sites (Quantitative Trait Loci - QTL) & their Effect Sizes on Component Traits;- Column 1: QTL Effect Sizes For Propensity To Tiller (ptt)- Column 2: QTL Effect Sizes For Canopy (ams)- Column 3: QTL Effect Sizes For Maturity (mtu) *QtlIndex.csv*Information on QTL position for each Component Trait. Position Number connects to Column order in qtl.csv- Column 1: Per Component Trait QTL Index- Column 2: QTL Positions For Propensity To Tiller (ptt)- Column 3: QTL Positions For Canopy (ams)- Column 4: QTL Positions For Maturity (mtu) *qtl.csv*Information on Number of Gene Copies (Alleles) at each QTL for each individual- 1st Column: Individual ID- 2nd Column Onnwards: QTL Allele Counts *markers.csv*Information on the number of Gene Copies (Alleles) at each SNP (Non-Causal Genomic Sites) for each individual- 1st Column: Individual ID- 2nd Column Onwards: SNP Allele Counts ##### Trait Records *trait_data.csv*Trait Records for each individual- Column 1: Genotype ID- Column 2: Phenotype (without error) for Propensity of Tiller (ptt)- Column 3: Phenotype (without error) for Canopy (ams)- Column 4: Phenotype (without error) for Maturity (mtu)- Column 5: Plant Population/Plot Density- Column 6: Environment/Site where Crop was grown- Column 7: Phenotype (without error) for Biomass- Column 8: Phenotype (without error) for Grain Yield *trait_data_H2_0.3.csv*Trait Records for each individual- Columns 1- 8: same as trait_data.csv- Column 9: Replicate ID- Column 10: Simulated Error for Grain Yield Observations in Column 11- Column 11: Phenotype (with error) for Grain Yield (Broad Sense Heritability=0.3) *trait_data_H2_0.5.csv*Trait Records for each individual- Columns 1- 8: same as trait_data.csv- Column 9: Replicate ID- Column 10: Simulated Error for Grain Yield Observations in Column 11- Column 11: Phenotype (with error) for Grain Yield (Broad Sense Heritability=0.5) *trait_data_H2_0.8.csv*Trait Records for each individual- Columns 1- 8: same as trait_data.csv- Column 9: Replicate ID- Column 10: Simulated Error for Grain Yield Observations in Column 11- Column 11: Phenotype (with error) for Grain Yield (Broad Sense Heritability=0.8) *trait_data_H2_0.99.csv*Trait Records for each individual- Columns 1- 8: same as trait_data.csv- Column 9: Replicate ID- Column 10: Simulated Error for Grain Yield Observations in Column 11- Column 11: Phenotype (with error) for Grain Yield (Broad Sense Heritability=0.99)

# 用于预测算法比较的计算机模拟高粱GxExM数据集
## 背景
本数据集为模拟多环境试验（Multi-Environment Trial, MET）数据集，旨在推动植物育种领域中解析基因型-环境-管理互作的预测算法的开发与比较。数据集涵盖多性状的基因组数据，包含单核苷酸多态性（Single Nucleotide Polymorphisms, SNP）与数量性状位点（Quantitative Trait Loci, QTL）相关信息，以及表型数据。
### 数据
##### 映射文件
map.csv
包含染色体内部及跨染色体的因果（数量性状位点QTL）与非因果（单核苷酸多态性SNP）基因组位点的位置信息。
列1：染色体编号
列2：标记ID
列3：位置（摩根单位）
##### 基因型数据
qtl_effects.csv
包含因果基因组位点（数量性状位点QTL）及其对各组分性状的效应量信息：
列1：分蘖倾向（Propensity To Tiller, ptt）的QTL效应量
列2：冠层性状（Canopy, ams）的QTL效应量
列3：生育期（Maturity, mtu）的QTL效应量

QtlIndex.csv
包含各组分性状的QTL位置信息，位置编号与qtl.csv中的列顺序一一对应：
列1：各组分性状的QTL索引
列2：分蘖倾向（ptt）的QTL位置
列3：冠层性状（ams）的QTL位置
列4：生育期（mtu）的QTL位置

qtl.csv
包含每个个体在各QTL位点的基因拷贝数（等位基因）信息：
第1列：个体ID
第2列及后续列：QTL等位基因计数

markers.csv
包含每个个体在各SNP（非因果基因组位点）位点的基因拷贝数（等位基因）信息：
第1列：个体ID
第2列及后续列：SNP等位基因计数

##### 性状记录文件
trait_data.csv
包含每个个体的性状记录：
列1：基因型ID
列2：分蘖倾向（ptt）的无误差表型值
列3：冠层性状（ams）的无误差表型值
列4：生育期（mtu）的无误差表型值
列5：植株群体/小区密度
列6：作物种植的环境/试验地点
列7：生物量的无误差表型值
列8：籽粒产量的无误差表型值

trait_data_H2_0.3.csv
包含每个个体的性状记录：
列1至8：与trait_data.csv完全一致
列9：重复ID
列10：第11列籽粒产量观测值的模拟误差项
列11：籽粒产量的带误差表型值（广义遗传力=0.3）

trait_data_H2_0.5.csv
包含每个个体的性状记录：
列1至8：与trait_data.csv完全一致
列9：重复ID
列10：第11列籽粒产量观测值的模拟误差项
列11：籽粒产量的带误差表型值（广义遗传力=0.5）

trait_data_H2_0.8.csv
包含每个个体的性状记录：
列1至8：与trait_data.csv完全一致
列9：重复ID
列10：第11列籽粒产量观测值的模拟误差项
列11：籽粒产量的带误差表型值（广义遗传力=0.8）

trait_data_H2_0.99.csv
包含每个个体的性状记录：
列1至8：与trait_data.csv完全一致
列9：重复ID
列10：第11列籽粒产量观测值的模拟误差项
列11：籽粒产量的带误差表型值（广义遗传力=0.99）