Trained PriLer models on European ancestry individuals

Prior learned elastic-net regression (PriLer) gene expression models trained on reference panels GTEx v6p and CMC release 1. Inside each folder, "genotype_info/" include tab-separated files divided per chromosome with info on variants used to train the models. "tissues/" include trained models divided per tissue. In the corresponding folders,<strong> resPrior_regEval_allchr.txt</strong> is a tab-separated file with summary statistics of trained model for each gene, sorted by chromosome and position. <strong>resPrior_regCoeffSnps_allchr.RData </strong>is an RData object including a Sparse Matrix per chromosome n. variants x n. of genes with trained regression coefficients. Variants position match genotype files and gene position match gene summary statistic order (divided per chromosome). <strong>ENSEMBL_gene_SNP_2e+05_chrxx_matrix.mtx </strong>are sparse 0/1 matrices per chromosome n. variants x n. of genes that represent gene-variant distance matrices. For each gene, 1 indicates a variant being located in the transcription starting site window +/- 200kb. To use the trained model to impute gene expression from on genotype dosages, follow Module 2 workflow in of https://gitlab.mpcdf.mpg.de/luciat/castom-igex.git基于参考面板GTEx v6p与CMC Release 1训练得到的预训练弹性网回归（PriLer）基因表达模型。每个文件夹内的`genotype_info/`目录存储有按染色体拆分的制表符分隔文件，内含用于训练模型的变异位点信息；`tissues/`目录存储有按组织拆分的已训练模型。 在对应文件夹中，**resPrior_regEval_allchr.txt**为制表符分隔文件，内含所有基因的训练模型汇总统计信息，并按染色体与位点排序。**resPrior_regCoeffSnps_allchr.RData**为RData格式文件，内含按染色体拆分的稀疏矩阵，矩阵维度为变异位点数 × 基因数，存储训练得到的回归系数。变异位点的位置与基因型文件中的位置一致，基因位置则与按染色体拆分的基因汇总统计信息的排序一致。 **ENSEMBL_gene_SNP_2e+05_chrXX_matrix.mtx**为按染色体拆分的稀疏0/1矩阵，矩阵维度为变异位点数 × 基因数，用于表示基因-变异位点距离矩阵。对于每个基因而言，矩阵中的1代表该变异位点位于转录起始位点上下游200kb的窗口范围内。 若需利用训练好的模型基于基因型剂量数据推断基因表达量，请遵循https://gitlab.mpcdf.mpg.de/luciat/castom-igex.git 中的模块2工作流程进行操作。