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omicAnnotations

This package pools together information from different databases and APIs in order to annotate SNPs and genes. In particular this uses databases by:

EBI EMR enrichr ncbi gtex  pubmed   disgenet

To install:

devtools::install_github("KatrionaGoldmann/omicAnnotations")

Gene Annotations

First, if you want to include associated diseases from disGeNET you will need to get an api_key. To get this sign up and get your API key either from the API directly or run:

api_key <- get_api_key(email="your email", password="your password")

For example for the entire gene summary:

gene_df <- gene_summary(genes=c("MS4A1", "FMOD", "FGF1", "SLAMF6"), 
                        diseases="C20", 
                        disease_api_token=api_key)

## [1] "Annotating from self-curated data..."
## [1] "Getting gene summaries..."
## [1] "Finding associated diseases..."

gene_df <- gene_df[, c("Gene", "description", "summary", "Associated_diseases")]

kable(gene_df, format = "markdown", row.names = FALSE)
Gene description summary Associated_diseases
MS4A1 membrane spanning 4-domains A1 This gene encodes a member of the membrane-spanning 4A gene family. Members of this nascent protein family are characterized by common structural features and similar intron/exon splice boundaries and display unique expression patterns among hematopoietic cells and nonlymphoid tissues. This gene encodes a B-lymphocyte surface molecule which plays a role in the development and differentiation of B-cells into plasma cells. This family member is localized to 11q12, among a cluster of family members. Alternative splicing of this gene results in two transcript variants which encode the same protein. [provided by RefSeq, Jul 2008] Common Variable Immunodeficiency; Acquired Hypogammaglobulinemia; Immunoglobulin Deficiency, Late-Onset
FMOD fibromodulin Fibromodulin belongs to the family of small interstitial proteoglycans. The encoded protein possesses a central region containing leucine-rich repeats with 4 keratan sulfate chains, flanked by terminal domains containing disulphide bonds. Owing to the interaction with type I and type II collagen fibrils and in vitro inhibition of fibrillogenesis, the encoded protein may play a role in the assembly of extracellular matrix. It may also regulate TGF-beta activities by sequestering TGF-beta into the extracellular matrix. Sequence variations in this gene may be associated with the pathogenesis of high myopia. Alternative splicing results in multiple transcript variants. [provided by RefSeq, Jun 2013]
FGF1 fibroblast growth factor 1 The protein encoded by this gene is a member of the fibroblast growth factor (FGF) family. FGF family members possess broad mitogenic and cell survival activities, and are involved in a variety of biological processes, including embryonic development, cell growth, morphogenesis, tissue repair, tumor growth and invasion. This protein functions as a modifier of endothelial cell migration and proliferation, as well as an angiogenic factor. It acts as a mitogen for a variety of mesoderm- and neuroectoderm-derived cells in vitro, thus is thought to be involved in organogenesis. Multiple alternatively spliced variants encoding different isoforms have been described. [provided by RefSeq, Jan 2009]
SLAMF6 SLAM family member 6 The protein encoded by this gene is a type I transmembrane protein, belonging to the CD2 subfamily of the immunoglobulin superfamily. This encoded protein is expressed on Natural killer (NK), T, and B lymphocytes. It undergoes tyrosine phosphorylation and associates with the Src homology 2 domain-containing protein (SH2D1A) as well as with SH2 domain-containing phosphatases (SHPs). It functions as a coreceptor in the process of NK cell activation. It can also mediate inhibitory signals in NK cells from X-linked lymphoproliferative patients. Alternative splicing results in multiple transcript variants encoding distinct isoforms.[provided by RefSeq, May 2010]

Publications

You can check for publications focusing on genes with given terms. Either using associated_publications:

gene_pubs <- associated_publications(genes=c("FGF1"), 
                                     keywords=c("rheumatoid"), 
                                     split="OR", 
                                     verbose=TRUE)

kable(gene_pubs, format = "markdown", row.names=FALSE)
Gene Publications
FGF1 The transcriptomic profiling of SARS-CoV-2 compared to SARS, MERS, EBOV, and H1N1.; sICAM-1 as potential additional parameter in the discrimination of the Sjögren syndrome and non-autoimmune sicca syndrome: a pilot study.; [Effects of Huatan Tongluo Recipe on IL-1β-induced Proliferation of Rheumatoid Arthritis Synovial Fibroblasts and the Production of TNF-α and aFGF].; Fibroblast growth factors, fibroblast growth factor receptors, diseases, and drugs.; VEGF, FGF1, FGF2 and EGF gene polymorphisms and psoriatic arthritis.; Transcription factor Ets-1 regulates fibroblast growth factor-1-mediated angiogenesis in vivo: role of Ets-1 in the regulation of the PI3K/AKT/MMP-1 pathway.; Induction of RANKL expression and osteoclast maturation by the binding of fibroblast growth factor 2 to heparan sulfate proteoglycan on rheumatoid synovial fibroblasts.; Acidic fibroblast growth factor in synovial cells.; Characterization of tissue outgrowth developed in vitro in patients with rheumatoid arthritis: involvement of T cells in the development of tissue outgrowth.; Fibroblast growth factor-1 (FGF-1) enhances IL-2 production and nuclear translocation of NF-kappaB in FGF receptor-bearing Jurkat T cells.; A novel in vitro assay for human angiogenesis.; Expression and functional expansion of fibroblast growth factor receptor T cells in rheumatoid synovium and peripheral blood of patients with rheumatoid arthritis.; Detection of T cells responsive to a vascular growth factor in rheumatoid arthritis.; Coexpression of phosphotyrosine-containing proteins, platelet-derived growth factor-B, and fibroblast growth factor-1 in situ in synovial tissues of patients with rheumatoid arthritis and Lewis rats with adjuvant or streptococcal cell wall arthritis.; Platelet-derived growth factors and heparin-binding (fibroblast) growth factors in the synovial tissue pathology of rheumatoid arthritis.; Fibroblast growth factors: from genes to clinical applications.; Production of platelet derived growth factor B chain (PDGF-B/c-sis) mRNA and immunoreactive PDGF B-like polypeptide by rheumatoid synovium: coexpression with heparin binding acidic fibroblast growth factor-1.; Detection of high levels of heparin binding growth factor-1 (acidic fibroblast growth factor) in inflammatory arthritic joints.

Or gene_summary:

gene_df <- gene_summary(genes=c("FGF1"), 
                        associated_diseases =FALSE,
                        gene_description=FALSE, 
                        publications = TRUE)

## [1] "Annotating from self-curated data..."
## [1] "Getting publications from PubMed..."

kable(gene_df, format = "markdown", row.names=FALSE)
Gene Type Curated_description Publications
FGF1 Fibroblast Growth Factors FGF/FGFR Pathways in Multiple Sclerosis and in Its Disease Models.; The transcriptomic profiling of SARS-CoV-2 compared to SARS, MERS, EBOV, and H1N1.; sICAM-1 as potential additional parameter in the discrimination of the Sjögren syndrome and non-autoimmune sicca syndrome: a pilot study.; Oligodendroglial fibroblast growth factor receptor 1 gene targeting protects mice from experimental autoimmune encephalomyelitis through ERK/AKT phosphorylation.; [Effects of Huatan Tongluo Recipe on IL-1β-induced Proliferation of Rheumatoid Arthritis Synovial Fibroblasts and the Production of TNF-α and aFGF].; Dysregulation of pathways involved in the processing of cancer and microenvironment information in MCA + TPA transformed C3H/10T1/2 cells.; Fibroblast growth factors, fibroblast growth factor receptors, diseases, and drugs.; VEGF, FGF1, FGF2 and EGF gene polymorphisms and psoriatic arthritis.; Cutaneous gene expression by DNA microarray in murine sclerodermatous graft-versus-host disease, a model for human scleroderma.; Transcription factor Ets-1 regulates fibroblast growth factor-1-mediated angiogenesis in vivo: role of Ets-1 in the regulation of the PI3K/AKT/MMP-1 pathway.; Angiocidal effect of Cyclosporin A: a new therapeutic approach for pathogenic angiogenesis.; Induction of RANKL expression and osteoclast maturation by the binding of fibroblast growth factor 2 to heparan sulfate proteoglycan on rheumatoid synovial fibroblasts.; Acidic fibroblast growth factor in synovial cells.; Characterization of tissue outgrowth developed in vitro in patients with rheumatoid arthritis: involvement of T cells in the development of tissue outgrowth.; Lack of FGF-1 overexpression during autoimmune nephritis in the kidneys of MRL lpr/lpr mice.; Fibroblast growth factor-1 (FGF-1) enhances IL-2 production and nuclear translocation of NF-kappaB in FGF receptor-bearing Jurkat T cells.; Cloning and characterization of a novel upstream untranslated exon of the mouse Fgf-1 gene.; Cloning and characterization of the mouse Fgf-1 gene.; A novel in vitro assay for human angiogenesis.; Expression and functional expansion of fibroblast growth factor receptor T cells in rheumatoid synovium and peripheral blood of patients with rheumatoid arthritis.; Environmental influences on fatty acid composition of membranes from autoimmune MRL lpr/lpr mice.; Costimulation of human CD4+ T cells by fibroblast growth factor-1 (acidic fibroblast growth factor).; Detection of T cells responsive to a vascular growth factor in rheumatoid arthritis.; Coexpression of phosphotyrosine-containing proteins, platelet-derived growth factor-B, and fibroblast growth factor-1 in situ in synovial tissues of patients with rheumatoid arthritis and Lewis rats with adjuvant or streptococcal cell wall arthritis.; Platelet-derived growth factors and heparin-binding (fibroblast) growth factors in the synovial tissue pathology of rheumatoid arthritis.; Fibroblast growth factors: from genes to clinical applications.; Production of platelet derived growth factor B chain (PDGF-B/c-sis) mRNA and immunoreactive PDGF B-like polypeptide by rheumatoid synovium: coexpression with heparin binding acidic fibroblast growth factor-1.; Detection of high levels of heparin binding growth factor-1 (acidic fibroblast growth factor) in inflammatory arthritic joints.

Enriched pathways

Looks for enriched pathways with gene sets using enrichR.

lymphoid_pathways <- enriched_pathways(
  genes=c("LAMP5", "LINC01480", "FAM92B", "SLAMF6", "CEP128",
          "FKBP11", "CRTAM", "ISG20", "ZBP1", "TMEM229B",
          "FAM46C", "XBP1", "APOBEC3G", "TNIK", "CD2", "SP140",
          "ACOXL", "PTPRCAP", "PDCD1", "KCNN3", "GZMK",
          "IGFLR1", "SH2D2A", "PIM2", "TPST2"),
  libraries = c('Pathways'),
  dbs=NULL,
  check_for_updates = FALSE)

If that doesn’t work it may be because the website is down. This happens occasionally. You can check by using:

listEnrichrDbs()

Plots

lymphoid_pathways$plot

eQTL Catalogue

eqtl_table <- associated_eqtl(genes=c("ENSG00000164308"), p_cutoff=1)

## [1] "Looking at SNPs"
## [1] "Looking at Genes"

kable(eqtl_table, row.names=F)
rsid chromosome molecular\_trait\_id gene\_id tissue qtl\_group pvalue neg\_log10\_pvalue se beta median\_tpm study\_id type alt position ac maf variant ref r2 an
rs57584041 5 ENSG00000164308 ENSG00000164308 CL\_0000235 macrophage\_IFNg 0.142464 0.8462949 0.862435 1.2793100 14.576 Alasoo\_2018 SNP C 95877044 5 0.0297619 chr5\_95877044\_T\_C T 0.87667 168
rs6556892 5 ENSG00000164308 ENSG00000164308 CL\_0000235 macrophage\_IFNg 0.299611 0.5234422 0.338419 0.3536530 14.576 Alasoo\_2018 SNP A 95878071 56 0.3333330 chr5\_95878071\_C\_A C 0.92606 168
rs55763081 5 ENSG00000164308 ENSG00000164308 CL\_0000235 macrophage\_IFNg 0.324924 0.4882182 1.103560 -1.0940300 14.576 Alasoo\_2018 SNP G 95876702 3 0.0178571 chr5\_95876702\_A\_G A 0.81827 168
rs61540882 5 ENSG00000164308 ENSG00000164308 CL\_0000235 macrophage\_IFNg 0.325028 0.4880792 1.103460 -1.0936900 14.576 Alasoo\_2018 INDEL T 95876577 3 0.0178571 chr5\_95876577\_TAAA\_T TAAA 0.81754 168
rs796285486 5 ENSG00000164308 ENSG00000164308 CL\_0000235 macrophage\_IFNg 0.325028 0.4880792 1.103460 -1.0936900 14.576 Alasoo\_2018 INDEL T 95876577 3 0.0178571 chr5\_95876577\_TAAA\_T TAAA 0.81754 168
rs154457 5 ENSG00000164308 ENSG00000164308 CL\_0000235 macrophage\_IFNg 0.347034 0.4596280 0.376044 0.3560110 14.576 Alasoo\_2018 SNP A 95876181 130 0.2261900 chr5\_95876181\_G\_A G 0.93729 168
rs154458 5 ENSG00000164308 ENSG00000164308 CL\_0000235 macrophage\_IFNg 0.354738 0.4500923 0.375816 0.3501150 14.576 Alasoo\_2018 SNP T 95876288 130 0.2261900 chr5\_95876288\_C\_T C 0.94067 168
rs154456 5 ENSG00000164308 ENSG00000164308 CL\_0000235 macrophage\_IFNg 0.355252 0.4494635 0.375702 0.3496330 14.576 Alasoo\_2018 SNP T 95876161 130 0.2261900 chr5\_95876161\_A\_T A 0.94121 168
rs144088066 5 ENSG00000164308 ENSG00000164308 CL\_0000235 macrophage\_IFNg 0.358421 0.4456066 1.143510 -1.0571400 14.576 Alasoo\_2018 INDEL C 95878406 3 0.0178571 chr5\_95878406\_CTCT\_C CTCT 0.74292 168
rs17085223 5 ENSG00000164308 ENSG00000164308 CL\_0000235 macrophage\_IFNg 0.363755 0.4391910 1.139710 -1.0419100 14.576 Alasoo\_2018 SNP T 95877713 3 0.0178571 chr5\_95877713\_G\_T G 0.77062 168
rs113842599 5 ENSG00000164308 ENSG00000164308 CL\_0000235 macrophage\_IFNg 0.402339 0.3954079 1.153880 -0.9722280 14.576 Alasoo\_2018 SNP G 95878112 3 0.0178571 chr5\_95878112\_C\_G C 0.70249 168
rs749046156 5 ENSG00000164308 ENSG00000164308 CL\_0000235 macrophage\_IFNg 0.409355 0.3878999 0.958131 0.7952580 14.576 Alasoo\_2018 INDEL GT 95877403 5 0.0297619 chr5\_95877403\_G\_GT G 0.65265 168
rs397957177 5 ENSG00000164308 ENSG00000164308 CL\_0000235 macrophage\_IFNg 0.409355 0.3878999 0.958131 0.7952580 14.576 Alasoo\_2018 INDEL GT 95877403 5 0.0297619 chr5\_95877403\_G\_GT G 0.65265 168
rs1256088833 5 ENSG00000164308 ENSG00000164308 CL\_0000235 macrophage\_IFNg 0.482832 0.3162040 1.163830 -0.8210970 14.576 Alasoo\_2018 INDEL G 95877403 2 0.0119048 chr5\_95877403\_GT\_G GT 0.58191 168
rs111471052 5 ENSG00000164308 ENSG00000164308 CL\_0000235 macrophage\_IFNg 0.482832 0.3162040 1.163830 -0.8210970 14.576 Alasoo\_2018 INDEL G 95877403 2 0.0119048 chr5\_95877403\_GT\_G GT 0.58191 168
rs154454 5 ENSG00000164308 ENSG00000164308 CL\_0000235 macrophage\_IFNg 0.537536 0.2695924 0.385196 0.2386650 14.576 Alasoo\_2018 SNP G 95875943 133 0.2083330 chr5\_95875943\_C\_G C 0.96320 168
rs11372327 5 ENSG00000164308 ENSG00000164308 CL\_0000235 macrophage\_IFNg 0.710863 0.1482141 0.818859 -0.3047850 14.576 Alasoo\_2018 INDEL AC 95878741 162 0.0357143 chr5\_95878741\_A\_AC A 0.91136 168
rs397998782 5 ENSG00000164308 ENSG00000164308 CL\_0000235 macrophage\_IFNg 0.710863 0.1482141 0.818859 -0.3047850 14.576 Alasoo\_2018 INDEL AC 95878741 162 0.0357143 chr5\_95878741\_A\_AC A 0.91136 168
rs154459 5 ENSG00000164308 ENSG00000164308 CL\_0000235 macrophage\_IFNg 0.738887 0.1314220 0.332555 -0.1112910 14.576 Alasoo\_2018 SNP T 95876578 72 0.4285710 chr5\_95876578\_A\_T A 0.94702 168
rs154455 5 ENSG00000164308 ENSG00000164308 CL\_0000235 macrophage\_IFNg 0.803819 0.0948417 0.335028 -0.0835397 14.576 Alasoo\_2018 SNP T 95876057 74 0.4404760 chr5\_95876057\_C\_T C 0.96802 168

SNP Annotations

omicAnnotations can also be used to find out more info about SNPs.

GWAS Catalogue

gwas_traits <- associated_traits(snps = c("rs2910686", "rs7329174"))

kable(gwas_traits, row.names = F)
SNPs Associated\_traits
rs2910686 neutrophil count; ankylosing spondylitis; crohn’s disease; psoriasis; sclerosing cholangitis; ulcerative colitis
rs7329174 systemic lupus erythematosus; crohn’s disease

eQTL Catalogue

eqtl_table <- associated_eqtl(snps = c("rs2910686", "rs7329174"),
                              p_cutoff = 0.05)

## [1] "Looking at SNPs"
## [1] "Looking at Genes"

kable(eqtl_table, row.names = F)
rsid chromosome molecular\_trait\_id gene\_id tissue qtl\_group pvalue neg\_log10\_pvalue se beta median\_tpm study\_id type alt position ac maf variant ref r2 an
rs2910686 5 ENSG00000164308 ENSG00000164308 CL\_0000235 macrophage\_IFNg 0.0000000 32.033736 0.1084150 2.3491000 14.576 Alasoo\_2018 SNP C 96916885 68 0.4047620 rs2910686 T 0.99787 168
rs2910686 5 ENSG00000164308 ENSG00000164308 CL\_0000235 macrophage\_IFNg 0.0000000 28.094117 0.1188220 2.2120400 14.576 Alasoo\_2018 SNP C 96916885 68 0.4047620 rs2910686 T 0.99787 168
rs2910686 5 ENSG00000164307 ENSG00000164307 CL\_0000235 macrophage\_IFNg 0.0001333 3.875124 0.0474250 -0.1917860 50.151 Alasoo\_2018 SNP C 96916885 68 0.4047620 rs2910686 T 0.99787 168
rs7329174 13 ENSG00000102760 ENSG00000102760 UBERON\_0001013 adipose\_naive 0.0006357 3.196736 0.0714243 0.2470190 445.066 FUSION SNP G 40983974 38 0.0701107 rs7329174 A 1.00000 542
rs2910686 5 ENSG00000247121 ENSG00000247121 CL\_0000235 macrophage\_IFNg 0.0007469 3.126725 0.0779628 -0.2749620 1.260 Alasoo\_2018 SNP C 96916885 68 0.4047620 rs2910686 T 0.99787 168
rs2910686 5 ENSG00000164307 ENSG00000164307 CL\_0000235 macrophage\_IFNg 0.0008048 3.094338 0.0611752 -0.2143270 50.151 Alasoo\_2018 SNP C 96916885 68 0.4047620 rs2910686 T 0.99787 168
rs2910686 5 ENSG00000113441 ENSG00000113441 CL\_0000235 macrophage\_IFNg 0.0012984 2.886608 0.0291856 0.0978188 14.738 Alasoo\_2018 SNP C 96916885 68 0.4047620 rs2910686 T 0.99787 168
rs7329174 13 ENSG00000278390 ENSG00000278390 UBERON\_0009834 brain 0.0053281 2.273430 0.0627828 -0.1757720 3.801 BrainSeq SNP G 40983974 39 0.0407098 rs7329174 A 0.93510 958
rs7329174 13 ENSG00000102743 ENSG00000102743 UBERON\_0001013 adipose\_naive 0.0291754 1.534983 0.0500392 -0.1097560 3.886 FUSION SNP G 40983974 38 0.0701107 rs7329174 A 1.00000 542
rs2910686 5 ENSG00000113441 ENSG00000113441 CL\_0000235 macrophage\_naive 0.0482241 1.316736 0.0258004 0.0518735 14.738 Alasoo\_2018 SNP C 96916885 68 0.4047620 rs2910686 T 0.99787 168

GTex

g2s <- data.frame("Genes"=c("ERAP2", "ERAP2", "HLA-DRB9"), 
                  "Snps"=c("chr5_96916728_G_A", "chr5_96916885_T_C", 
                           "chr6_32620055_A_G"))

df <- gtex_eqtl(gene_snp_pairs = g2s)

library(ComplexHeatmap)

hm <- gtex_heatmap(df)
draw(hm, heatmap_legend_side = "left")