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Mapping gene regulatory networks from single-cell omics data
Abstract Single-cell techniques are advancing rapidly and are yielding unprecedented insight into cellular heterogeneity. Mapping the gene regulatory networks (GRNs) underlying cell states provides attractive opportunities to mechanistically understand this heterogeneity. In this review, we discuss...
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Published in: | Briefings in functional genomics 2018-07, Vol.17 (4), p.246-254 |
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container_title | Briefings in functional genomics |
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creator | Fiers, Mark W E J Minnoye, Liesbeth Aibar, Sara Bravo González-Blas, Carmen Kalender Atak, Zeynep Aerts, Stein |
description | Abstract
Single-cell techniques are advancing rapidly and are yielding unprecedented insight into cellular heterogeneity. Mapping the gene regulatory networks (GRNs) underlying cell states provides attractive opportunities to mechanistically understand this heterogeneity. In this review, we discuss recently emerging methods to map GRNs from single-cell transcriptomics data, tackling the challenge of increased noise levels and data sparsity compared with bulk data, alongside increasing data volumes. Next, we discuss how new techniques for single-cell epigenomics, such as single-cell ATAC-seq and single-cell DNA methylation profiling, can be used to decipher gene regulatory programmes. We finally look forward to the application of single-cell multi-omics and perturbation techniques that will likely play important roles for GRN inference in the future. |
doi_str_mv | 10.1093/bfgp/elx046 |
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Single-cell techniques are advancing rapidly and are yielding unprecedented insight into cellular heterogeneity. Mapping the gene regulatory networks (GRNs) underlying cell states provides attractive opportunities to mechanistically understand this heterogeneity. In this review, we discuss recently emerging methods to map GRNs from single-cell transcriptomics data, tackling the challenge of increased noise levels and data sparsity compared with bulk data, alongside increasing data volumes. Next, we discuss how new techniques for single-cell epigenomics, such as single-cell ATAC-seq and single-cell DNA methylation profiling, can be used to decipher gene regulatory programmes. We finally look forward to the application of single-cell multi-omics and perturbation techniques that will likely play important roles for GRN inference in the future.</description><identifier>ISSN: 2041-2649</identifier><identifier>ISSN: 2041-2657</identifier><identifier>EISSN: 2041-2657</identifier><identifier>DOI: 10.1093/bfgp/elx046</identifier><identifier>PMID: 29342231</identifier><language>eng</language><publisher>England: Oxford University Press</publisher><subject>Epigenomics - methods ; Gene Expression Profiling - methods ; Gene Regulatory Networks ; Sequence Analysis, RNA - methods ; Single-Cell Analysis - methods</subject><ispartof>Briefings in functional genomics, 2018-07, Vol.17 (4), p.246-254</ispartof><rights>The Author(s) 2018. Published by Oxford University Press. 2018</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c478t-b1a9a917d37c0d97952208ee23ae0da3407451ff5d31857e46fa0998a4dfeea13</citedby><cites>FETCH-LOGICAL-c478t-b1a9a917d37c0d97952208ee23ae0da3407451ff5d31857e46fa0998a4dfeea13</cites><orcidid>0000-0001-5694-2409</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,780,784,885,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/29342231$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Fiers, Mark W E J</creatorcontrib><creatorcontrib>Minnoye, Liesbeth</creatorcontrib><creatorcontrib>Aibar, Sara</creatorcontrib><creatorcontrib>Bravo González-Blas, Carmen</creatorcontrib><creatorcontrib>Kalender Atak, Zeynep</creatorcontrib><creatorcontrib>Aerts, Stein</creatorcontrib><title>Mapping gene regulatory networks from single-cell omics data</title><title>Briefings in functional genomics</title><addtitle>Brief Funct Genomics</addtitle><description>Abstract
Single-cell techniques are advancing rapidly and are yielding unprecedented insight into cellular heterogeneity. Mapping the gene regulatory networks (GRNs) underlying cell states provides attractive opportunities to mechanistically understand this heterogeneity. In this review, we discuss recently emerging methods to map GRNs from single-cell transcriptomics data, tackling the challenge of increased noise levels and data sparsity compared with bulk data, alongside increasing data volumes. Next, we discuss how new techniques for single-cell epigenomics, such as single-cell ATAC-seq and single-cell DNA methylation profiling, can be used to decipher gene regulatory programmes. We finally look forward to the application of single-cell multi-omics and perturbation techniques that will likely play important roles for GRN inference in the future.</description><subject>Epigenomics - methods</subject><subject>Gene Expression Profiling - methods</subject><subject>Gene Regulatory Networks</subject><subject>Sequence Analysis, RNA - methods</subject><subject>Single-Cell Analysis - methods</subject><issn>2041-2649</issn><issn>2041-2657</issn><issn>2041-2657</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>TOX</sourceid><recordid>eNp9kMtLw0AQxhdRbKk9eZecRJDYfeWxIIIUX1DxoudlmszGaJKNu4na_96UatGLc5mB-fHNNx8hh4yeMarEbGmKdobVJ5XxDhlzKlnI4yjZ3c5SjcjU-xc6lGBSMrpPRlwJyblgY3J-D21bNkVQYIOBw6KvoLNuFTTYfVj36gPjbB34AakwzLCqAluXmQ9y6OCA7BmoPE6_-4Q8XV89zm_DxcPN3fxyEWYySbtwyUCBYkkukozmKlER5zRF5AKQ5iAkTWTEjIlywdIoQRkboEqlIHODCExMyMVGt-2XNeYZNp2DSreurMGttIVS_9005bMu7LuOaSx4ogaBk28BZ9969J2uS79-Bhq0vddMpSpKo8HYgJ5u0MxZ7x2a7RlG9TpyvY5cbyIf6KPfzrbsT8ADcLwBbN_-q_QF_QiLgg</recordid><startdate>20180701</startdate><enddate>20180701</enddate><creator>Fiers, Mark W E J</creator><creator>Minnoye, Liesbeth</creator><creator>Aibar, Sara</creator><creator>Bravo González-Blas, Carmen</creator><creator>Kalender Atak, Zeynep</creator><creator>Aerts, Stein</creator><general>Oxford University Press</general><scope>TOX</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0001-5694-2409</orcidid></search><sort><creationdate>20180701</creationdate><title>Mapping gene regulatory networks from single-cell omics data</title><author>Fiers, Mark W E J ; Minnoye, Liesbeth ; Aibar, Sara ; Bravo González-Blas, Carmen ; Kalender Atak, Zeynep ; Aerts, Stein</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c478t-b1a9a917d37c0d97952208ee23ae0da3407451ff5d31857e46fa0998a4dfeea13</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Epigenomics - methods</topic><topic>Gene Expression Profiling - methods</topic><topic>Gene Regulatory Networks</topic><topic>Sequence Analysis, RNA - methods</topic><topic>Single-Cell Analysis - methods</topic><toplevel>online_resources</toplevel><creatorcontrib>Fiers, Mark W E J</creatorcontrib><creatorcontrib>Minnoye, Liesbeth</creatorcontrib><creatorcontrib>Aibar, Sara</creatorcontrib><creatorcontrib>Bravo González-Blas, Carmen</creatorcontrib><creatorcontrib>Kalender Atak, Zeynep</creatorcontrib><creatorcontrib>Aerts, Stein</creatorcontrib><collection>Oxford Academic Journals (Open Access)</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Briefings in functional genomics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Fiers, Mark W E J</au><au>Minnoye, Liesbeth</au><au>Aibar, Sara</au><au>Bravo González-Blas, Carmen</au><au>Kalender Atak, Zeynep</au><au>Aerts, Stein</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Mapping gene regulatory networks from single-cell omics data</atitle><jtitle>Briefings in functional genomics</jtitle><addtitle>Brief Funct Genomics</addtitle><date>2018-07-01</date><risdate>2018</risdate><volume>17</volume><issue>4</issue><spage>246</spage><epage>254</epage><pages>246-254</pages><issn>2041-2649</issn><issn>2041-2657</issn><eissn>2041-2657</eissn><abstract>Abstract
Single-cell techniques are advancing rapidly and are yielding unprecedented insight into cellular heterogeneity. Mapping the gene regulatory networks (GRNs) underlying cell states provides attractive opportunities to mechanistically understand this heterogeneity. In this review, we discuss recently emerging methods to map GRNs from single-cell transcriptomics data, tackling the challenge of increased noise levels and data sparsity compared with bulk data, alongside increasing data volumes. Next, we discuss how new techniques for single-cell epigenomics, such as single-cell ATAC-seq and single-cell DNA methylation profiling, can be used to decipher gene regulatory programmes. We finally look forward to the application of single-cell multi-omics and perturbation techniques that will likely play important roles for GRN inference in the future.</abstract><cop>England</cop><pub>Oxford University Press</pub><pmid>29342231</pmid><doi>10.1093/bfgp/elx046</doi><tpages>9</tpages><orcidid>https://orcid.org/0000-0001-5694-2409</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Epigenomics - methods Gene Expression Profiling - methods Gene Regulatory Networks Sequence Analysis, RNA - methods Single-Cell Analysis - methods |
title | Mapping gene regulatory networks from single-cell omics data |
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