{"id":3084,"date":"2015-01-20T14:48:56","date_gmt":"2015-01-20T13:48:56","guid":{"rendered":"http:\/\/news.embl.de\/?p=3084"},"modified":"2024-11-29T16:55:29","modified_gmt":"2024-11-29T15:55:29","slug":"1501-cell-types","status":"publish","type":"post","link":"https:\/\/www.embl.org\/news\/science\/1501-cell-types\/","title":{"rendered":"Hidden cell types revealed"},"content":{"rendered":"\n<p class=\"p1\">A new method for analysing RNA sequence data allows researchers to identify new subtypes of cells, creating order out of seeming chaos. <a href=\"http:\/\/dx.doi.org\/%2010.1038\/nbt.3102\">Published in <i>Nature Biotechnology<\/i><\/a>, the novel technique developed by scientists at EMBL-EBI represents a major step forward for single-cell genomics.<\/p>\n\n\n\n<p class=\"p1\">Single-cell RNA-sequencing is a relatively new technology that helps scientists understand how genes are expressed in different types of healthy tissue and in cancers. It provides data on the gene-expression profiles of hundreds of individual cells in a single experiment, producing an exact picture of the individual cell types. However, the fundamental complexity of single-cell transcriptome profiles has posed a major challenge to making sense of the data.<\/p>\n\n\n\n<p class=\"p1\">\u201cWith single-cell genomics, we take cells from a tissue and group them into different types based on their expression profile, identifying subtypes that may have a range of functional roles. But to do that properly, we need to deal with confounding factors, and until now we haven\u2019t had robust methods for doing that,\u201d explains <a href=\"http:\/\/www.ebi.ac.uk\/research\/marioni\">John Marioni, Research Group Leader <\/a>at EMBL-EB<a href=\"http:\/\/www.ebi.ac.uk\/research\/marioni\">I<\/a>.<\/p>\n\n\n\n<blockquote class=\"vf-blockquote\"><p class=\"p1\">The analysis of single cell types is essential for medical research&#8230;<\/p><\/blockquote>\n\n\n\n<p class=\"p1\">A sample from one type of tissue has built-in complexity: some cells will be new and some old, and at any given point in time they will be at different stages of the cell cycle. Most cell types also have hidden sub-types, each of which may have a distinct function. The new single-cell latent variable model (scLVM) allows hidden sub-structure to be detected and controlled for, thereby allowing relevant biological signals to be more easily identified.<\/p>\n\n\n\n<p class=\"p1\">\u201cWe\u2019ve defined how factors such as cell-cycle stage, measurement noise or biological processes can be taken into account, making it possible to create a more accurate picture of gene expression in different cell types and subtypes,\u201d says Florian B\u00fcttner, who led the research at EMBL-EBI as an EMBO Visiting Scientist from the Institute of Computational Biology at Helmholtz Zentrum M\u00fcnchen. \u201cCombining single-cell analyses with statistical methods lets us identify cell types that would otherwise remain undetected.\u201d<\/p>\n\n\n\n<p class=\"p1\">\u201cIf all you have is gene expression data from single cells, you need a way to identify and correct for the underlying factors that differentiate individual cells, so you can reveal the underlying biology,\u201d explains <a href=\"http:\/\/www.ebi.ac.uk\/research\/stegle\">Oliver Stegle, Research Group Leader <\/a>at EMBL-EBI.<span class=\"Apple-converted-space\">&nbsp; <\/span>\u201cOur model accounts for relatedness between single cells, for example whether they are at the same stage of the cell cycle, identifies potentially confounding variables and removes them. It also makes it easier to find new subtypes \u2013 variables you might not have known existed \u2013 and correct for them, all at one go.\u201d<\/p>\n\n\n\n<p class=\"p1\">\u201cThe analysis of single cell types is essential for medical research,\u201d asserts B\u00fcttner. \u201cCancer cells, differentiation processes and the pathogenesis of various diseases can be better explored and understood when they are based only on known, detailed cell profiles. Our model now makes it possible to create such profiles using single-cell genomics.\u201d<span class=\"Apple-converted-space\">&nbsp;<\/span><\/p>\n\n\n\n<p><em>This post was originally published on <a href=\"https:\/\/www.ebi.ac.uk\/about\/news\/press-releases\/hidden-cell-types-revealed\" target=\"_blank\" rel=\"canonical nofollow noopener noreferrer\" data-href=\"https:\/\/www.ebi.ac.uk\/about\/news\/press-releases\/hidden-cell-types-revealed\">EMBL-EBI News.<\/a><\/em><\/p>\n","protected":false},"excerpt":{"rendered":"<p>New statistical method for RNA-seq analysis creates order out of seeming chaos.<\/p>\n","protected":false},"author":13,"featured_media":3087,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[2,17591],"tags":[408],"embl_taxonomy":[],"class_list":["post-3084","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-science","category-science-technology","tag-marioni"],"acf":{"article_intro":"<p><i>A new statistical method for RNA-seq analysis identifies and corrects for hidden structure between cells, creating order out of seeming chaos.<\/i><\/p>\n","related_links":[{"link_description":"Blog post by Ewan Birney, 19 January 2015: Untangling Big Data","link_url":"http:\/\/genomeinformatician.blogspot.co.uk\/2015\/01\/untangling-big-data.html"}],"article_sources":[{"source_description":"<p>Buettner, F. <em>et al.\u00a0Nature Biotechnology,<\/em>\u00a0published online 19 January 2015. DOI: 10.1038\/nbt.3102<\/p>\n","source_link_url":"http:\/\/www.nature.com\/nbt\/journal\/vaop\/ncurrent\/full\/nbt.3102.html"}],"vf_locked":false,"featured":false,"color":"#007B53"},"embl_taxonomy_terms":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.2 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Hidden cell types revealed | EMBL<\/title>\n<meta name=\"description\" content=\"A new statistical method for RNA-seq analysis identifies and corrects for hidden structure between cells, creating order out of seeming chaos.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.embl.org\/news\/science\/1501-cell-types\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Hidden cell types revealed | EMBL\" \/>\n<meta property=\"og:description\" content=\"A new statistical method for RNA-seq analysis identifies and corrects for hidden structure between cells, creating order out of seeming chaos.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.embl.org\/news\/science\/1501-cell-types\/\" \/>\n<meta property=\"og:site_name\" content=\"EMBL\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/embl.org\/\" \/>\n<meta property=\"article:author\" content=\"www.facebook.com\/EMBLEBI\" \/>\n<meta property=\"article:published_time\" content=\"2015-01-20T13:48:56+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2024-11-29T15:55:29+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.embl.org\/news\/wp-content\/uploads\/2015\/01\/Marioni_CellNews_EMBL-e1421833839440.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"620\" \/>\n\t<meta property=\"og:image:height\" content=\"424\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"Mary Todd Bergman\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@EMBLEBI\" \/>\n<meta name=\"twitter:site\" content=\"@embl\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Mary Todd Bergman\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"2 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"NewsArticle\",\"@id\":\"https:\/\/www.embl.org\/news\/science\/1501-cell-types\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/www.embl.org\/news\/science\/1501-cell-types\/\"},\"author\":{\"name\":\"Mary Todd Bergman\",\"@id\":\"https:\/\/www.embl.org\/news\/#\/schema\/person\/052a43af2beb3860bffa67c0f0474875\"},\"headline\":\"Hidden cell types revealed\",\"datePublished\":\"2015-01-20T13:48:56+00:00\",\"dateModified\":\"2024-11-29T15:55:29+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/www.embl.org\/news\/science\/1501-cell-types\/\"},\"wordCount\":499,\"publisher\":{\"@id\":\"https:\/\/www.embl.org\/news\/#organization\"},\"image\":{\"@id\":\"https:\/\/www.embl.org\/news\/science\/1501-cell-types\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/www.embl.org\/news\/wp-content\/uploads\/2015\/01\/Marioni_CellNews_EMBL-e1421833839440.jpg\",\"keywords\":[\"marioni\"],\"articleSection\":[\"Science\",\"Science &amp; 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