{"id":846,"date":"2022-06-02T15:48:12","date_gmt":"2022-06-02T15:48:12","guid":{"rendered":"https:\/\/www.embl.org\/groups\/zaugg\/?page_id=846"},"modified":"2023-05-09T23:33:17","modified_gmt":"2023-05-09T23:33:17","slug":"resources-enhancer-mediated-gene-regulatory-networks","status":"publish","type":"page","link":"https:\/\/www.embl.org\/groups\/zaugg\/data-and-tools\/resources-enhancer-mediated-gene-regulatory-networks\/","title":{"rendered":"Resources: GRaNIE and GRaNPA: Inference and evaluation of enhancer-mediated gene regulatory networks applied to study macrophages"},"content":{"rendered":"\n<p>Among the biggest challenges in the post-GWAS (genome-wide association studies) era is the interpretation of disease-associated genetic variants in non-coding genomic regions. Enhancers have emerged as key players in mediating the effect of genetic variants on complex traits and diseases. Their activity is regulated by a combination of transcription factors (TFs), epigenetic changes and genetic variants. Several approaches exist to link enhancers to their target genes, and others that infer TF-gene connections. However, we currently lack a framework that systematically integrates enhancers into TF-gene regulatory networks. Furthermore, we lack an unbiased way of assessing whether inferred regulatory interactions are biologically meaningful. Here we present two methods, implemented as user-friendly R-packages, for building and evaluating enhancer-mediated gene regulatory networks (eGRNs) called GRaNIE (Gene Regulatory Network Inference including Enhancers &#8211;\u00a0<a href=\"https:\/\/git.embl.de\/grp-zaugg\/GRaNIE\">https:\/\/git.embl.de\/grp-zaugg\/GRaNIE<\/a>) and GRaNPA (Gene Regulatory Network Performance Analysis &#8211;\u00a0<a href=\"https:\/\/git.embl.de\/grp-zaugg\/GRaNPA\">https:\/\/git.embl.de\/grp-zaugg\/GRaNPA<\/a>), respectively. GRaNIE jointly infers TF-enhancer, enhancer-gene and TF-gene interactions by integrating open chromatin data such as ATAC-Seq or H3K27ac with RNA-seq across a set of samples (e.g. individuals), and optionally also Hi-C data. GRaNPA is a general framework for evaluating the biological relevance of TF-gene GRNs by assessing their performance for predicting cell-type specific differential expression. We demonstrate the power of our tool-suite by investigating gene regulatory mechanisms in macrophages that underlie their response to infection, and their involvement in common genetic diseases including autoimmune diseases.<\/p>\n\n\n\n<p><em>Resources:<\/em><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><a rel=\"noreferrer noopener\" href=\"https:\/\/www.bioconductor.org\/packages\/release\/bioc\/html\/GRaNIE.html\" target=\"_blank\">Link to GRaNIE R-package<\/a>&nbsp;for creating enhancer-mediated gene regulatory networks<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li><a rel=\"noreferrer noopener\" href=\"https:\/\/grp-zaugg.embl-community.io\/GRaNPA\/\" target=\"_blank\">Link to GRaNPA R-package<\/a> for testing the predictive power of gene regulatory networks<\/li>\n<\/ul>\n\n\n\n<ul class=\"wp-block-list\">\n<li><a rel=\"noreferrer noopener\" href=\"https:\/\/apps.embl.de\/grn\/\" target=\"_blank\">Link to shiny app for some pre-existing eGRNs<\/a><\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>Among the biggest challenges in the post-GWAS (genome-wide association studies) era is the interpretation of disease-associated genetic variants in non-coding genomic regions. Enhancers have emerged as key players in mediating the effect of genetic variants on complex traits and diseases. Their&hellip;<\/p>\n","protected":false},"author":10,"featured_media":0,"parent":816,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"footnotes":""},"embl_taxonomy":[],"class_list":["post-846","page","type-page","status-publish","hentry"],"acf":[],"embl_taxonomy_terms":[],"_links":{"self":[{"href":"https:\/\/www.embl.org\/groups\/zaugg\/wp-json\/wp\/v2\/pages\/846","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.embl.org\/groups\/zaugg\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.embl.org\/groups\/zaugg\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.embl.org\/groups\/zaugg\/wp-json\/wp\/v2\/users\/10"}],"replies":[{"embeddable":true,"href":"https:\/\/www.embl.org\/groups\/zaugg\/wp-json\/wp\/v2\/comments?post=846"}],"version-history":[{"count":3,"href":"https:\/\/www.embl.org\/groups\/zaugg\/wp-json\/wp\/v2\/pages\/846\/revisions"}],"predecessor-version":[{"id":7612,"href":"https:\/\/www.embl.org\/groups\/zaugg\/wp-json\/wp\/v2\/pages\/846\/revisions\/7612"}],"up":[{"embeddable":true,"href":"https:\/\/www.embl.org\/groups\/zaugg\/wp-json\/wp\/v2\/pages\/816"}],"wp:attachment":[{"href":"https:\/\/www.embl.org\/groups\/zaugg\/wp-json\/wp\/v2\/media?parent=846"}],"wp:term":[{"taxonomy":"embl_taxonomy","embeddable":true,"href":"https:\/\/www.embl.org\/groups\/zaugg\/wp-json\/wp\/v2\/embl_taxonomy?post=846"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}