Manual curation of burden tests from key publications and resources.
Associations of 9 genes with schizophrenia. The data is pulled from their downloads page (https://schema.broadinstitute.org/downloads).
Associations of 2 genes with epilepsy. The data is pulled from their downloads page (https://epi25.broadinstitute.org/downloads).
Associations of 21 genes with different metabolomics measurements. The data is pulled from 2 sites: - Table 1 of their manuscript provides the key metrics. - The sheet named "strongest gene/metabolite" in the Supplementary Table 5 provides annotation of nº samples.
Associations of 3 genes with chronic kidney disease. The data is pulled from 2 locations: - Table 2 of their publication (https://jasn.asnjournals.org/content/jnephrol/30/6/1109.full.pdf?with-ds=yes). - Supplementary Table 5 provides annotation of nº samples.
Associations of 102 genes with autism. The data is pulled from the Supplementary Table 2 in their publication (https://www.sciencedirect.com/science/article/pii/S0092867419313984#mmc2).
Associations of 497 genes with traits from the UK Biobank. The data has been parsed from the Supplementary Table 2, 3, and 4 of their publication (https://www.nature.com/articles/s41586-021-04103-z) + the mappings done by GWAS Catalog.
Associations of 60 genes with autism were identified by analyzing de novo and rare inherited variants from WES and WGS data. The data is pulled from the results of the meta analysis described in the Supplementary Table 9 of their publication (https://www.nature.com/articles/s41588-022-01148-2). Only associations with a p-value < 2.5 × 10−6 are included.
16 genes associated with fat distribution (BMI-adjusted WHR) were identified by analysing missense variants from WES data. Most of them with a protective direction of effect. The data is pulled from the Table 1 of their publication (https://www.nature.com/articles/s41467-022-32398-7.pdf). Only associations with a p-value < 3.6 × 10−7 are included.
9 genes associated with Parkinson disease were identified by analysing rare variants from WES and WGS data of different cohorts. The data is curated from Table 1 (data about the population) and Table 2 and 3 (https://www.medrxiv.org/content/10.1101/2022.11.08.22280168v1.full). We report the results of the meta analyses when they show exome wide significance, otherwise we show the significant result on the independent sample.
16 genes associated with 226 NMR biomarkers of the lipid metabolism that are relevant in cardiovascular disase. The meta-analysis was done on individuals from the INTERVAL cohort based on WES and WGS data that was oylled from the Supplementary Table 2 (aggregation of LOF variants) and Supplementary Table 3 (aggregation of LOF and deleterious missense variants) (https://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1008605#sec019). The significance threshold of the meta-analysis is set at 2.5E-6.