DOI: 10.5281/zenodo.5745927
title: Significant eQTLs and expression TWAS reference panels (AMP-AD brain and EADB Belgian LCL cohorts)

description: This dataset is part of the manuscript "<em><strong>New insights into the genetic etiology of Alzheimer’s disease and related dementias</strong></em>" by Bellenguez, Küçükali, et al. Nature Genetics 2022. Publication link: https://www.nature.com/articles/s41588-022-01024-z GitHub repository of all QTL/TWAS data shared for this study: https://github.com/SleegersLab-VIBCMN/EADB_GWAS_NatureGenetics_QTL_TWAS For details, please see the publication. For any questions, please contact Fahri Küçükali (fahri.kucukali@uantwerpen.vib.be) and Kristel Sleegers (Kristel.Sleegers@uantwerpen.vib.be). Significant eQTL catalogues are compressed with <em>gzip </em>and tar achieve of expression TWAS reference panels are compressed with <em>bzip2</em>. <strong>eQTL catalogues</strong> The files show significant eQTL - gene pairs mapped in AMP-AD brain and EADB Belgian LCL cohorts. The catalogues are in hg38/GRCh38 human genome build. Most of the columns in the files are based on FastQTL output (http://fastqtl.sourceforge.net/). <em>eQTL file columns:</em> variant_id - ID of the significant eQTL variant based on the dbSNPv151 rsID annotation or hg38/GRCh38 CHR_POS_REF_ALT ID if rsID not available. gene_id - eGene ENSG gene ID based on GENCODEv24 (AMP-AD) or GENCODEv32 (EADB Belgian) tss_distance - Genomic distance between eQTL variant and eGene ma_samples - Number of samples carrying the minor allele ma_count - Total count of minor alleles maf - Minor allele frequency pval_nominal - Nominal <em>P</em>-value of the association slope - Slope of the association with respect to alternative (ALT) allele indicated on column 14 slope_se - Standard error of the slope pval_nominal_threshold - Nominal <em>P</em>-value significant threshold for this eGene min_pval_nominal - Most significant <em>P</em>-value observed for this eGene pval_beta - permutation <em>P</em>-value obtained via beta approximation and later used to calculate Storey q-values gene_name - eGene name based on GENCODEv24 (AMP-AD) and GENCODEv32 (EADB Belgian) GRCh38_chr_pos - Genomic position of the variant, separated by underscore ref_alt - Reference (REF) and alternative (ALT) allele of the variant, separated by "&gt;" sign. ALT is the tested (A1) allele Of note, we also mapped the significant sQTLs in the same datasets (please see the data availability section of the manuscript or the GitHub repository). <strong>Expression TWAS reference panels</strong> Custom expression TWAS reference panels prepared using FUSION pipeline (http://gusevlab.org/projects/fusion/) in AMP-AD brain and EADB Belgian LCL cohorts. All data in hg38/GRCh38 genome build. In each directory, you will find ".pos", ."profile", and ".profile.err" files. These are explained in the FUSION website as well, but briefly these are: <strong>.pos:</strong> This is a position file that describes the 1Mb extended gene start and end coordinates for each calculated weight file for each gene expression phenotype. Used for scanning the variants in those coordinates for TWAS. <strong>.profile: </strong>This informs about all prediction weights calculated, in terms of number of variants in the model, heritability information, and R2 info for each prediction model used (top1, blup, enet, bslmm, lasso; bslmm was not used therefore has NA values). <strong>.profile.err: </strong>This summarizes the reference panel in terms of average hsq (with SD), and which model is the best performing. Each TWAS weight is provided in a .RDat file under <strong>All_Expression_Weights</strong>, and in this data we included all calculated functional weights independent of the fact that they are heritable features or not. In our TWAS analyses, we included the heritable functional weights at a hsq <em>P</em>-value ≤ 0.05 level. Please also see the splicing TWAS reference panels we prepared in the same datasets (see the data availability section of the manuscript or the GitHub repository). If you need an LD reference data in hg38/GRCh38 genome build based on 1000 Genomes NFE samples (whose variant ID annotation are matching to these functional weights), suitable for running the TWAS/FUSION pipeline, please contact us.