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MetaXcan's Results
Alvaro Barbeira edited this page Jan 20, 2017
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The output of metaxcan is a text file that looks like the following:
gene,gene_name,zscore,effect_size,pvalue,VAR_g,pred_perf_R2,pred_perf_p,pred_perf_q,n_snps_used,n_snps_in_cov,n_snps_in_model
ENSG00000150938,CRIM1,-4.19069760413,-0.231471478373,2.78098095601e-05,0.0983344808163,0.13320775358,1.97496173512e-30,7.47907447189e-30,37,37,37
...
Each row will contain information for a successfully processed gene, formatted as:
- gene: a gene's id: as listed in the Tissue Transcriptome model. Ensemble Id for some, while some others (mainly DGN Whole Blood) provide Genquant's gene name
- gene_name: gene name as listed by the Transcriptome Model, generally extracted from Genquant
- zscore: MetaXcan's association result for the gene
- effect_size: MetaXcan's association effect size for the gene
- pvalue: P-value of the aforementioned statistic.
- pred_perf_r2: R2 of tissue model's correlation to gene's measured transcriptome (prediction performance)
- pred_perf_pval: pval of tissue model's correlation to gene's measured transcriptome (prediction performance)
- pred_perf_qval: qval of tissue model's correlation to gene's measured transcriptome (prediction performance)
- n_snps_used: number of snps from GWAS that got used in MetaXcan analysis
- n_snps_in_cov: number of snps in the covariance matrix
- n_snps_in_model: number of snps in the model
- var_g: variance of the gene expression, calculated as W' * G * W (where W is the vector of SNP weights in a gene's model, W' is its transpose, and G is the covariance matrix)