For scRNA-seq datasets in cell type analysis section, please see tutorial for links and references.
Data source/tool Used for Links Last update Reference
1000 genoms project Phase 3 Reference panel used to compute r2 and MAF. Info: http://www.internationalgenome.org/
Data: ftp://ftp.1000genomes.ebi.ac.uk/vol1/ftp/release/20130502/
5 December 2016 1000 Genomes Project Consortium, et al. 2015. A global reference for human genetic variation. Nature. 526, 68-74.
PMID:26432245
PLINK Used to compute r2 and MAF. Info and download: https://www.cog-genomics.org/plink2 5 December 2016 Purcell, S., et al. 2007. PLINK: A tool set for whole-genome association and population-based linkage analyses. Am. J. Hum. Genet. 81, 559-575.
PMID:17701901
MAGMA Used for gene analysis and gene-set analysis. Info and download: https://ctg.cncr.nl/software/magma 30 Jan 2017 de Leeuw, C., et al. 2015. MAGMA: Generalized gene-set analysis of GWAS data. PLoS Comput. Biol. 11, DOI:10.1371/journal.pcbi.1004219.
PMCID:PMC4401657
ANNOVAR A variant annotation tool used to obtain functional consequences of SNPs on gene functions. Info and download: http://annovar.openbioinformatics.org/en/latest/ 5 December 2016 Wang, K., Li, M. and Hakonarson, H. 2010. ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res. 38:e164
PMID:20601685
CADD v1.3 A deleterious score of variants computed by integrating 63 functional annotations. The higher the score, the more deleterious. Info: http://cadd.gs.washington.edu/
Data: http://cadd.gs.washington.edu/download
5 December 2016 Kicher, M., et al. 2014. A general framework for estimating the relative pathogeneticity of human genetic variants. Nat. Genet. 46, 310-315.
PMID:24487276
RegulomeDB v1.1 A categorical score to guide interpretation of regulatory variants. Info: http://regulomedb.org/index
Data: http://regulomedb.org/downloads/RegulomeDB.dbSNP141.txt.gz
5 December 2016 Boyle, AP., et al. 2012. Annotation of functional variation in personal genomes using RegulomeDB. Genome Res. 22, 1790-7.
PMID:22955989
15-core chromatin state Chromatin state for 127 epigenomes was learned by ChromHMM derived from 5 chromatin markers (H3K4me3, H3K4me1, H3K36me3, H3K27me3, H3K9me3). Info: http://egg2.wustl.edu/roadmap/web_portal/chr_state_learning.html
Data: http://egg2.wustl.edu/roadmap/data/byFileType/chromhmmSegmentations/ChmmModels/coreMarks/jointModel/final/all.mnemonics.bedFiles.tgz
5 December 2016 Roadmap Epigenomics Consortium, et al. 2015. Integrative analysis of 111 reference human epigenomes. Nature. 518, 317-330.
PMID:25693563
Ernst, J. and Kellis, M. 2012. ChromHMM: automating chromatin-state discovery and characterization. Nat. Methods. 28, 215-6.
PMID:22373907
GTEx v6/v7 eQTLs and gene expression used in the pipeline were obtained from GTEx v6.
For gene expression 53 tissue types are available and 44 for v6 and 48 for v7 of those which have more than 70 samples are included in eQTL analyses.
Info and data: http://www.gtexportal.org/home/ 21 January 2018 GTEx Consortium. 2015. Human genomics, The genotype-tissue expression (GTEx) pilot analysis: multitissue gene regulation in humans. Science. 348, 648-60.
PMID:25954001
GTEx Consortium. 2017. Genetic effects on gene expression across human tissues. Nature. 550, 204-213.
PMID:29022597
Blood eQTL Browser eQTLs of blood cells. Only cis-eQTLs with FDR ≤ 0.05 are available in FUMA. Info and data: http://genenetwork.nl/bloodeqtlbrowser/ 17 January 2017 Westra et al. 2013. Systematic identification of trans eQTLs as putative divers of known disease associations. Nat. Genet. 45, 1238-1243.
PMID:24013639
BIOS QTL browser eQTLs of blood cells in Dutch population. Only cis-eQTLs (gene-level) with FDR ≤ 0.05 are available in FUMA. Info and data: http://genenetwork.nl/biosqtlbrowser/ 17 January 2017 Zhernakova et al. 2017. Identification of context-dependent expression quantitative trait loci in whole blood. Nat. Genet. 49, 139-145.
PMID:27918533
BRAINEAC eQTLs of 10 brain regions. Cis-eQTLs with nominal P-value < 0.05 are available in FUMA. Info and data: http://www.braineac.org/ 26 January 2017 Ramasamy et al. 2014. Genetic variability in the regulation of gene expression in ten regions of the human brain. Nat. Neurosci. 17, 1418-1428.
PMID:27918533
MuTHER eQTLs in Adipose, LCL and Skin samples (only cis eQTLs). Info: http://www.muther.ac.uk/
Data: http://www.muther.ac.uk/Data.html
21 January 2018 Grundberg et al. 2012. Mapping cis and trans regulatory effects across multiple tissues in twins. Nat. Genet. 44, 1084-1089.
PMID:22941192
xQTLServer eQTLs in dorsolateral prefrontal cortex samples. Info and data: http://mostafavilab.stat.ubc.ca/xqtl/ 21 January 2018 Ng et al. 2017. An xQTL map integrates the genetic architecture of the human brain's transcriptome and epigenome. Nat. Neurosci. 20, 1418-1426.
PMID:28869584
CommonMind Consortium eQTLs in brain samples. Both cis and trans eQTLs are available Info and data: https://www.synapse.org//#!Synapse:syn5585484 21 January 2018 Fromer et al. 2016. Gene expression elucidates functional impact of polygenic risk for schizophrenia. Nat. Neurosci. 16, 1442-1453.
PMID:27668389
eQTLGen Meta-analysis of cis and trans eQTLs based on 37 data sets (in total of 31,684 individuals). Info: http://www.eqtlgen.org/index.html
Data: https://molgenis26.gcc.rug.nl/downloads/eqtlgen/cis-eqtl/cis-eQTLs_full_20180905.txt.gz, https://molgenis26.gcc.rug.nl/downloads/eqtlgen/trans-eqtl/trans-eQTL_significant_20181017.txt.gz
20 Oct 2018 Vosa et al. 2018. Unraveling the polygenic architecture of complex traits using blood eQTL meta-analysis. bioRxiv
https://doi.org/10.1101/447367
BrainSpan Gene expression data of developmental brain samples. Info and data: http://www.brainspan.org/static/download 31 January 2018 Miller et al. 2014. Transcriptional landscape of the prenatal human brain. Nature 508, 199-206.
PMID:24695229
GSE87112 (Hi-C) Hi-C data (significant loops) of 21 tissue/cell types. Pre-processed data (output of Fit-Hi-C) is used in FUMA. Info and data: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE87112 9 May 2017 Schmitt, A.D. et al. 2016. A compendium of chromatin contact maps reveals spatially active regions in the human genome. Cell Rep. 17, 2042-2059.
PMID:27851967
Enhancer and promoter regions Predicted enhancer and promoter regions (including dyadic) from Roadmap Epigenomics Projects. 111 epigenomes are available. Info: http://egg2.wustl.edu/roadmap/web_portal/DNase_reg.html
Data: http://egg2.wustl.edu/roadmap/data/byDataType/dnase/
9 May 2017 Roadmap Epigenomics Consortium, et al. 2015. Integrative analysis of 111 reference human epigenomes. Nature. 518, 317-330.
PMID:25693563
Ernst, J. and Kellis, M. 2012. ChromHMM: automating chromatin-state discovery and characterization. Nat. Methods. 28, 215-6.
PMID:22373907
MsigDB v6.1 Collection of publicly available gene sets. Data sets include e.g. KEGG, Reactome, BioCarta, GO terms and so on. Info and data: http://software.broadinstitute.org/gsea/msigdb 27 April 2018 Liberzon, A. et al. 2011. Molecular signatures database (MSigDB) 3.0. Bioinformatics. 27, 1739-40.
PMID:21546393
WikiPathways The curated biological pathways. Info: http://wikipathways.org/index.php/WikiPathways
Data: http://data.wikipathways.org/20161110/gmt/wikipathways-20161110-gmt-Homo_sapiens.gmt
5 December 2016 Kutmon, M., et al. 2016. WikiPathways: capturing the full diversity of pahtway knowledge. Nucleic Acids Res. 44, 488-494.
PMID:26481357
GWAS-catalog e91 2018-02-06 A database of reported snp-trait associations. Info: https://www.ebi.ac.uk/gwas/
Data: https://www.ebi.ac.uk/gwas/docs/downloads
12 February 2018 MacArthur, J., et al. 2016. The new NHGRI-EBI Catalog of published genome-wide association studies (GWAS Catalog). Nucleic Acids Res. pii:gkw1133.
PMID:27899670
DrugBank Targeted genes (protein) of drugs in DrugBank was obtained to assign drug ID for input genes. Info: https://www.ncbi.nlm.nih.gov/pubmed/27899670
Data: https://www.drugbank.ca/releases/latest#protein-identifiers
5 December 2016 Wishart, DS., et al. 2008. DrugBank: a knowledgebase for drugs, drug actions and drug targets. Nucleic Acis Res. 36, D901-6.
PMID:18048412
pLI A gene score annotated to prioritized genes. The score is the probability of being loss-of-function intolerance. Info: http://exac.broadinstitute.org/
Data: ftp://ftp.broadinstitute.org/pub/ExAC_release/release0.3.1/functional_gene_constraint
27 April 2017 Lek, M. et al. 2016. Analyses of protein-coding genetic variation in 60,706 humans. Nature. 536, 285-291.
PMID:27535533
ncRVIS A gene score annotated to prioritized genes. The score is the non-coding residual variation intolerance score. Info: http://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1005492
Data: http://journals.plos.org/plosgenetics/article/file?type=supplementary&id=info:doi/10.1371/journal.pgen.1005492.s011
27 April 2017 Petrovski, S. et al. 2015. The intolerance of regulatory sequence to genetic variation predict gene dosage sensitivity. PLOS Genet. 11, e1005492.
PMID:26332131