{"id":39048,"date":"2026-02-25T11:19:55","date_gmt":"2026-02-25T10:19:55","guid":{"rendered":"https:\/\/immunostep.com\/?p=39048"},"modified":"2026-02-04T11:38:00","modified_gmt":"2026-02-04T10:38:00","slug":"spreading-error-as-an-experimental-variable-how-to-quantify-it-and-use-it-to-optimize-cytometry-panels","status":"publish","type":"post","link":"https:\/\/immunostep.com\/es\/2026\/02\/25\/spreading-error-as-an-experimental-variable-how-to-quantify-it-and-use-it-to-optimize-cytometry-panels\/","title":{"rendered":"Spreading error as an experimental variable: How to quantify it and use it to optimize cytometry panels"},"content":{"rendered":"<p data-start=\"321\" data-end=\"913\">In high-dimensional <a href=\"https:\/\/immunostep.com\/?v=12470fe406d4\"><strong data-start=\"341\" data-end=\"359\">flow cytometry<\/strong>,<\/a> the concept of <strong data-start=\"376\" data-end=\"395\">spreading error<\/strong> is often mentioned in passing. Most discussions focus on <strong data-start=\"453\" data-end=\"466\">spillover<\/strong>, the classical overlap of fluorochrome emission spectra, but <strong data-start=\"528\" data-end=\"572\">spreading error is a distinct phenomenon<\/strong> with critical experimental consequences. Treating it as a <strong data-start=\"631\" data-end=\"671\">quantifiable and actionable variable<\/strong> can greatly enhance panel design, improve detection of rare populations, and optimize clinical endpoints. Despite its importance, very few technical blogs explore <strong data-start=\"835\" data-end=\"877\">spreading error as a measurable factor<\/strong> that informs experimental strategy.<\/p>\n<h2 data-start=\"920\" data-end=\"986\">From spillover to spreading error: Understanding the difference<\/h2>\n<p data-start=\"988\" data-end=\"1445\">While <strong data-start=\"994\" data-end=\"1007\">spillover<\/strong> refers to the signal of one fluorochrome bleeding into a neighboring detector channel, <strong data-start=\"1095\" data-end=\"1114\">spreading error<\/strong> reflects the <strong data-start=\"1128\" data-end=\"1175\">statistical uncertainty in signal detection<\/strong> caused by this spillover. Even when compensation is applied perfectly, spreading error introduces additional variance in fluorescence measurements. This variance can <strong data-start=\"1342\" data-end=\"1380\">mask subtle phenotypic differences<\/strong> or create artificial dispersion in multi-dimensional analyses.<\/p>\n<p data-start=\"1447\" data-end=\"1755\">Understanding this distinction is essential for high-dimensional panels, where multiple <strong data-start=\"1535\" data-end=\"1567\">bright and dim fluorochromes<\/strong> interact. Ignoring spreading error can lead to <strong data-start=\"1615\" data-end=\"1651\">misinterpretation of populations<\/strong>, particularly <strong data-start=\"1666\" data-end=\"1698\">rare or low-frequency events<\/strong> that are crucial for translational and clinical studies.<\/p>\n<h2 data-start=\"1762\" data-end=\"1815\">Quantifying spreading error before closing a panel<\/h2>\n<p data-start=\"1817\" data-end=\"1994\">A key advantage of treating spreading error as a <strong data-start=\"1866\" data-end=\"1889\">measurable variable<\/strong> is the ability to <strong data-start=\"1908\" data-end=\"1961\">predict its impact before finalizing panel design<\/strong>. Practical strategies include:<\/p>\n<ul data-start=\"1996\" data-end=\"2411\">\n<li data-start=\"1996\" data-end=\"2129\">\n<p data-start=\"1998\" data-end=\"2129\"><strong data-start=\"1998\" data-end=\"2033\">Single-stained control analysis<\/strong> to compute the <strong data-start=\"2049\" data-end=\"2102\">coefficient of variation contributed by spillover<\/strong> in neighboring channels.<\/p>\n<\/li>\n<li data-start=\"2130\" data-end=\"2261\">\n<p data-start=\"2132\" data-end=\"2261\"><a href=\"https:\/\/flowjo.com\/docs\/flowjo10\/experiment-based-platforms\/plat-comp-overview\/spillover-spreading-matrix\"><strong data-start=\"2132\" data-end=\"2170\">Spillover spreading matrices (SSM)<\/strong>,<\/a> which provide a channel-by-channel assessment of spreading error for each fluorochrome.<\/p>\n<\/li>\n<li data-start=\"2262\" data-end=\"2411\">\n<p data-start=\"2264\" data-end=\"2411\">Simulation approaches, where virtual populations are analyzed to <strong data-start=\"2329\" data-end=\"2379\">estimate the masking effect of spreading error<\/strong> on rare population detection.<\/p>\n<\/li>\n<\/ul>\n<p data-start=\"2413\" data-end=\"2626\">By incorporating these analyses <strong data-start=\"2445\" data-end=\"2476\">prior to panel finalization<\/strong>, researchers can identify fluorochrome combinations that <strong data-start=\"2534\" data-end=\"2555\">minimize variance<\/strong> in critical channels, rather than discovering issues post-acquisition.<\/p>\n<h2 data-start=\"2633\" data-end=\"2685\">Impact on rare populations and clinical endpoints<\/h2>\n<p data-start=\"2687\" data-end=\"2997\"><strong data-start=\"2687\" data-end=\"2737\">Spreading error can have outsized consequences<\/strong> when detecting <strong data-start=\"2753\" data-end=\"2773\">rare populations<\/strong>, such as <strong data-start=\"2783\" data-end=\"2862\">antigen-specific T cells, CAR-T subsets, or early immune activation markers<\/strong>. Small increases in variance may <strong data-start=\"2896\" data-end=\"2919\">obscure these cells<\/strong>, leading to <strong data-start=\"2932\" data-end=\"2964\">underestimation of frequency<\/strong> or <strong data-start=\"2968\" data-end=\"2994\">false-negative results<\/strong>.<\/p>\n<p data-start=\"2999\" data-end=\"3408\">In clinical studies, where <strong data-start=\"3026\" data-end=\"3060\">endpoint accuracy is paramount<\/strong>, spreading error can distort both <strong data-start=\"3095\" data-end=\"3123\">biomarker quantification<\/strong> and <strong data-start=\"3128\" data-end=\"3151\">functional readouts<\/strong>, affecting <strong data-start=\"3163\" data-end=\"3209\">decision-making and patient stratification<\/strong>. By treating spreading error as an <strong data-start=\"3245\" data-end=\"3270\">experimental variable<\/strong>, researchers can anticipate these pitfalls and <strong data-start=\"3318\" data-end=\"3365\">design panels that preserve signal fidelity<\/strong>, even in complex, multi-color experiments.<\/p>\n<h2 data-start=\"3415\" data-end=\"3465\">When adding a marker can make the dataset worse<\/h2>\n<p data-start=\"3467\" data-end=\"3716\">One counterintuitive but critical insight is that <strong data-start=\"3517\" data-end=\"3546\">adding a new fluorochrome<\/strong>\u2014even for a seemingly low-priority marker\u2014can <strong data-start=\"3592\" data-end=\"3628\">increase overall spreading error<\/strong> and degrade the performance of the entire panel. This effect is most pronounced when:<\/p>\n<ul data-start=\"3718\" data-end=\"3950\">\n<li data-start=\"3718\" data-end=\"3798\">\n<p data-start=\"3720\" data-end=\"3798\">The new fluorochrome emits in a <strong data-start=\"3752\" data-end=\"3795\">channel adjacent to a critical detector<\/strong>.<\/p>\n<\/li>\n<li data-start=\"3799\" data-end=\"3862\">\n<p data-start=\"3801\" data-end=\"3862\">It is highly bright relative to the population of interest.<\/p>\n<\/li>\n<li data-start=\"3863\" data-end=\"3950\">\n<p data-start=\"3865\" data-end=\"3950\">The panel is already <strong data-start=\"3886\" data-end=\"3906\">high-dimensional<\/strong>, with multiple overlapping fluorochromes.<\/p>\n<\/li>\n<\/ul>\n<p data-start=\"3952\" data-end=\"4169\">Recognizing this, panel designers must <strong data-start=\"3991\" data-end=\"4078\">weigh the value of additional markers against their contribution to spreading error<\/strong>, ensuring that each addition improves experimental outcomes rather than compromising them.<\/p>\n<h2 data-start=\"4176\" data-end=\"4226\">Conclusion: Making spreading error work for you<\/h2>\n<p data-start=\"4228\" data-end=\"4442\">Treating <strong data-start=\"4237\" data-end=\"4296\">spreading error as a quantifiable experimental variable<\/strong> transforms it from a nuisance into a <strong data-start=\"4334\" data-end=\"4365\">tool for panel optimization<\/strong>. By measuring, simulating, and anticipating its effects, cytometrists can:<\/p>\n<ul data-start=\"4444\" data-end=\"4613\">\n<li data-start=\"4444\" data-end=\"4488\">\n<p data-start=\"4446\" data-end=\"4488\">Reduce variance in <strong data-start=\"4465\" data-end=\"4486\">critical channels<\/strong><\/p>\n<\/li>\n<li data-start=\"4489\" data-end=\"4543\">\n<p data-start=\"4491\" data-end=\"4543\">Preserve the detectability of <strong data-start=\"4521\" data-end=\"4541\">rare populations<\/strong><\/p>\n<\/li>\n<li data-start=\"4544\" data-end=\"4613\">\n<p data-start=\"4546\" data-end=\"4613\">Maintain <strong data-start=\"4555\" data-end=\"4611\">data integrity in clinical and translational studies<\/strong><\/p>\n<\/li>\n<\/ul>\n<p data-start=\"4615\" data-end=\"4907\">Despite its technical complexity, <strong data-start=\"4649\" data-end=\"4702\">spreading error is not just a theoretical concept<\/strong>. Expert handling of this variable allows researchers to <strong data-start=\"4759\" data-end=\"4833\">design more robust, reproducible, and high-performing cytometry panels<\/strong>, turning what is usually an invisible problem into a strategic advantage.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>In high-dimensional flow cytometry, the concept of spreading error is often mentioned in passing. Most discussions focus on spillover, the classical overlap of fluorochrome emission spectra, but spreading error is a distinct phenomenon with critical experimental consequences. Treating it as a quantifiable and actionable variable can greatly enhance panel design, improve detection of rare populations, [&hellip;]<\/p>\n","protected":false},"author":225,"featured_media":39051,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":"","_links_to":"","_links_to_target":""},"categories":[2033],"tags":[2489,2488,2487,2490,2491,2486],"class_list":["post-39048","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-immunology","tag-high-dimensional-flow-cytometry","tag-panel-optimization-in-cytometry","tag-quantifying-spreading-error","tag-rare-population-detection","tag-spillover-vs-spreading-error","tag-spreading-error-in-flow-cytometry"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v23.6 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Spreading error as an experimental variable: How to quantify it and use it to optimize cytometry panels | Immunostep Biotech<\/title>\n<meta name=\"description\" content=\"At Immunostep we have been innovating since 2001 to develop comprehensive products that contribute to improve.- Experimental-\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/immunostep.com\/2026\/02\/25\/spreading-error-as-an-experimental-variable-how-to-quantify-it-and-use-it-to-optimize-cytometry-panels\/\" \/>\n<meta property=\"og:locale\" content=\"es_ES\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Spreading error as an experimental variable: How to quantify it and use it to optimize cytometry panels | Immunostep Biotech\" \/>\n<meta property=\"og:description\" content=\"At Immunostep we have been innovating since 2001 to develop comprehensive products that contribute to improve.- Experimental-\" \/>\n<meta property=\"og:url\" content=\"https:\/\/immunostep.com\/2026\/02\/25\/spreading-error-as-an-experimental-variable-how-to-quantify-it-and-use-it-to-optimize-cytometry-panels\/\" \/>\n<meta property=\"og:site_name\" content=\"Immunostep Biotech\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/immunostepsl\/\" \/>\n<meta property=\"article:published_time\" content=\"2026-02-25T10:19:55+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2026-02-04T10:38:00+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/immunostep.com\/wp-content\/uploads\/2026\/02\/Spreading-error-as-an-experimental-variable.png\" \/>\n\t<meta property=\"og:image:width\" content=\"900\" \/>\n\t<meta property=\"og:image:height\" content=\"600\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"author\" content=\"\u00c1ngela Cabestrero\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@Immunostep\" \/>\n<meta name=\"twitter:site\" content=\"@Immunostep\" \/>\n<meta name=\"twitter:label1\" content=\"Escrito por\" \/>\n\t<meta name=\"twitter:data1\" content=\"\u00c1ngela Cabestrero\" \/>\n\t<meta name=\"twitter:label2\" content=\"Tiempo de lectura\" \/>\n\t<meta name=\"twitter:data2\" content=\"3 minutos\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/immunostep.com\/2026\/02\/25\/spreading-error-as-an-experimental-variable-how-to-quantify-it-and-use-it-to-optimize-cytometry-panels\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/immunostep.com\/2026\/02\/25\/spreading-error-as-an-experimental-variable-how-to-quantify-it-and-use-it-to-optimize-cytometry-panels\/\"},\"author\":{\"name\":\"\u00c1ngela Cabestrero\",\"@id\":\"https:\/\/immunostep.com\/#\/schema\/person\/6f7086a7900eb41588a2465bcae5f427\"},\"headline\":\"Spreading error as an experimental variable: How to quantify it and use it to optimize cytometry panels\",\"datePublished\":\"2026-02-25T10:19:55+00:00\",\"dateModified\":\"2026-02-04T10:38:00+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/immunostep.com\/2026\/02\/25\/spreading-error-as-an-experimental-variable-how-to-quantify-it-and-use-it-to-optimize-cytometry-panels\/\"},\"wordCount\":590,\"publisher\":{\"@id\":\"https:\/\/immunostep.com\/#organization\"},\"image\":{\"@id\":\"https:\/\/immunostep.com\/2026\/02\/25\/spreading-error-as-an-experimental-variable-how-to-quantify-it-and-use-it-to-optimize-cytometry-panels\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/immunostep.com\/wp-content\/uploads\/2026\/02\/Spreading-error-as-an-experimental-variable.png\",\"keywords\":[\"high-dimensional flow cytometry\",\"panel optimization in cytometry\",\"quantifying spreading error\",\"rare population detection\",\"spillover vs spreading error\",\"spreading error in flow cytometry\"],\"articleSection\":[\"Immunology\"],\"inLanguage\":\"es\"},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/immunostep.com\/2026\/02\/25\/spreading-error-as-an-experimental-variable-how-to-quantify-it-and-use-it-to-optimize-cytometry-panels\/\",\"url\":\"https:\/\/immunostep.com\/2026\/02\/25\/spreading-error-as-an-experimental-variable-how-to-quantify-it-and-use-it-to-optimize-cytometry-panels\/\",\"name\":\"Spreading error as an experimental variable: How to quantify it and use it to optimize cytometry panels | Immunostep Biotech\",\"isPartOf\":{\"@id\":\"https:\/\/immunostep.com\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\/\/immunostep.com\/2026\/02\/25\/spreading-error-as-an-experimental-variable-how-to-quantify-it-and-use-it-to-optimize-cytometry-panels\/#primaryimage\"},\"image\":{\"@id\":\"https:\/\/immunostep.com\/2026\/02\/25\/spreading-error-as-an-experimental-variable-how-to-quantify-it-and-use-it-to-optimize-cytometry-panels\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/immunostep.com\/wp-content\/uploads\/2026\/02\/Spreading-error-as-an-experimental-variable.png\",\"datePublished\":\"2026-02-25T10:19:55+00:00\",\"dateModified\":\"2026-02-04T10:38:00+00:00\",\"description\":\"At Immunostep we have been innovating since 2001 to develop comprehensive products that contribute to improve.- Experimental-\",\"breadcrumb\":{\"@id\":\"https:\/\/immunostep.com\/2026\/02\/25\/spreading-error-as-an-experimental-variable-how-to-quantify-it-and-use-it-to-optimize-cytometry-panels\/#breadcrumb\"},\"inLanguage\":\"es\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/immunostep.com\/2026\/02\/25\/spreading-error-as-an-experimental-variable-how-to-quantify-it-and-use-it-to-optimize-cytometry-panels\/\"]}]},{\"@type\":\"ImageObject\",\"inLanguage\":\"es\",\"@id\":\"https:\/\/immunostep.com\/2026\/02\/25\/spreading-error-as-an-experimental-variable-how-to-quantify-it-and-use-it-to-optimize-cytometry-panels\/#primaryimage\",\"url\":\"https:\/\/immunostep.com\/wp-content\/uploads\/2026\/02\/Spreading-error-as-an-experimental-variable.png\",\"contentUrl\":\"https:\/\/immunostep.com\/wp-content\/uploads\/2026\/02\/Spreading-error-as-an-experimental-variable.png\",\"width\":900,\"height\":600,\"caption\":\"Spreading error as an experimental variable\"},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/immunostep.com\/2026\/02\/25\/spreading-error-as-an-experimental-variable-how-to-quantify-it-and-use-it-to-optimize-cytometry-panels\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\/\/immunostep.com\/es\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Spreading error as an experimental variable: How to quantify it and use it to optimize cytometry panels\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/immunostep.com\/#website\",\"url\":\"https:\/\/immunostep.com\/\",\"name\":\"Immunostep Biotech\",\"description\":\"Innovating to deliver high-performance technology for Research and Diagnosis\",\"publisher\":{\"@id\":\"https:\/\/immunostep.com\/#organization\"},\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/immunostep.com\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"es\"},{\"@type\":\"Organization\",\"@id\":\"https:\/\/immunostep.com\/#organization\",\"name\":\"Immunostep Biotech\",\"url\":\"https:\/\/immunostep.com\/\",\"logo\":{\"@type\":\"ImageObject\",\"inLanguage\":\"es\",\"@id\":\"https:\/\/immunostep.com\/#\/schema\/logo\/image\/\",\"url\":\"https:\/\/immunostep.com\/wp-content\/uploads\/2021\/10\/logo-web-color.png\",\"contentUrl\":\"https:\/\/immunostep.com\/wp-content\/uploads\/2021\/10\/logo-web-color.png\",\"width\":1299,\"height\":591,\"caption\":\"Immunostep Biotech\"},\"image\":{\"@id\":\"https:\/\/immunostep.com\/#\/schema\/logo\/image\/\"},\"sameAs\":[\"https:\/\/www.facebook.com\/immunostepsl\/\",\"https:\/\/x.com\/Immunostep\",\"https:\/\/www.linkedin.com\/company\/immunostepsl\/\"]},{\"@type\":\"Person\",\"@id\":\"https:\/\/immunostep.com\/#\/schema\/person\/6f7086a7900eb41588a2465bcae5f427\",\"name\":\"\u00c1ngela Cabestrero\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"es\",\"@id\":\"https:\/\/immunostep.com\/#\/schema\/person\/image\/\",\"url\":\"https:\/\/secure.gravatar.com\/avatar\/378033e78b9b0300f6f50aeac830c5cf?s=96&d=mm&r=g\",\"contentUrl\":\"https:\/\/secure.gravatar.com\/avatar\/378033e78b9b0300f6f50aeac830c5cf?s=96&d=mm&r=g\",\"caption\":\"\u00c1ngela Cabestrero\"},\"url\":\"https:\/\/immunostep.com\/es\/author\/acabestrero\/\"}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"Spreading error as an experimental variable: How to quantify it and use it to optimize cytometry panels | Immunostep Biotech","description":"At Immunostep we have been innovating since 2001 to develop comprehensive products that contribute to improve.- Experimental-","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/immunostep.com\/2026\/02\/25\/spreading-error-as-an-experimental-variable-how-to-quantify-it-and-use-it-to-optimize-cytometry-panels\/","og_locale":"es_ES","og_type":"article","og_title":"Spreading error as an experimental variable: How to quantify it and use it to optimize cytometry panels | Immunostep Biotech","og_description":"At Immunostep we have been innovating since 2001 to develop comprehensive products that contribute to improve.- Experimental-","og_url":"https:\/\/immunostep.com\/2026\/02\/25\/spreading-error-as-an-experimental-variable-how-to-quantify-it-and-use-it-to-optimize-cytometry-panels\/","og_site_name":"Immunostep Biotech","article_publisher":"https:\/\/www.facebook.com\/immunostepsl\/","article_published_time":"2026-02-25T10:19:55+00:00","article_modified_time":"2026-02-04T10:38:00+00:00","og_image":[{"width":900,"height":600,"url":"https:\/\/immunostep.com\/wp-content\/uploads\/2026\/02\/Spreading-error-as-an-experimental-variable.png","type":"image\/png"}],"author":"\u00c1ngela Cabestrero","twitter_card":"summary_large_image","twitter_creator":"@Immunostep","twitter_site":"@Immunostep","twitter_misc":{"Escrito por":"\u00c1ngela Cabestrero","Tiempo de lectura":"3 minutos"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"Article","@id":"https:\/\/immunostep.com\/2026\/02\/25\/spreading-error-as-an-experimental-variable-how-to-quantify-it-and-use-it-to-optimize-cytometry-panels\/#article","isPartOf":{"@id":"https:\/\/immunostep.com\/2026\/02\/25\/spreading-error-as-an-experimental-variable-how-to-quantify-it-and-use-it-to-optimize-cytometry-panels\/"},"author":{"name":"\u00c1ngela Cabestrero","@id":"https:\/\/immunostep.com\/#\/schema\/person\/6f7086a7900eb41588a2465bcae5f427"},"headline":"Spreading error as an experimental variable: How to quantify it and use it to optimize cytometry panels","datePublished":"2026-02-25T10:19:55+00:00","dateModified":"2026-02-04T10:38:00+00:00","mainEntityOfPage":{"@id":"https:\/\/immunostep.com\/2026\/02\/25\/spreading-error-as-an-experimental-variable-how-to-quantify-it-and-use-it-to-optimize-cytometry-panels\/"},"wordCount":590,"publisher":{"@id":"https:\/\/immunostep.com\/#organization"},"image":{"@id":"https:\/\/immunostep.com\/2026\/02\/25\/spreading-error-as-an-experimental-variable-how-to-quantify-it-and-use-it-to-optimize-cytometry-panels\/#primaryimage"},"thumbnailUrl":"https:\/\/immunostep.com\/wp-content\/uploads\/2026\/02\/Spreading-error-as-an-experimental-variable.png","keywords":["high-dimensional flow cytometry","panel optimization in cytometry","quantifying spreading error","rare population detection","spillover vs spreading error","spreading error in flow cytometry"],"articleSection":["Immunology"],"inLanguage":"es"},{"@type":"WebPage","@id":"https:\/\/immunostep.com\/2026\/02\/25\/spreading-error-as-an-experimental-variable-how-to-quantify-it-and-use-it-to-optimize-cytometry-panels\/","url":"https:\/\/immunostep.com\/2026\/02\/25\/spreading-error-as-an-experimental-variable-how-to-quantify-it-and-use-it-to-optimize-cytometry-panels\/","name":"Spreading error as an experimental variable: How to quantify it and use it to optimize cytometry panels | Immunostep Biotech","isPartOf":{"@id":"https:\/\/immunostep.com\/#website"},"primaryImageOfPage":{"@id":"https:\/\/immunostep.com\/2026\/02\/25\/spreading-error-as-an-experimental-variable-how-to-quantify-it-and-use-it-to-optimize-cytometry-panels\/#primaryimage"},"image":{"@id":"https:\/\/immunostep.com\/2026\/02\/25\/spreading-error-as-an-experimental-variable-how-to-quantify-it-and-use-it-to-optimize-cytometry-panels\/#primaryimage"},"thumbnailUrl":"https:\/\/immunostep.com\/wp-content\/uploads\/2026\/02\/Spreading-error-as-an-experimental-variable.png","datePublished":"2026-02-25T10:19:55+00:00","dateModified":"2026-02-04T10:38:00+00:00","description":"At Immunostep we have been innovating since 2001 to develop comprehensive products that contribute to improve.- Experimental-","breadcrumb":{"@id":"https:\/\/immunostep.com\/2026\/02\/25\/spreading-error-as-an-experimental-variable-how-to-quantify-it-and-use-it-to-optimize-cytometry-panels\/#breadcrumb"},"inLanguage":"es","potentialAction":[{"@type":"ReadAction","target":["https:\/\/immunostep.com\/2026\/02\/25\/spreading-error-as-an-experimental-variable-how-to-quantify-it-and-use-it-to-optimize-cytometry-panels\/"]}]},{"@type":"ImageObject","inLanguage":"es","@id":"https:\/\/immunostep.com\/2026\/02\/25\/spreading-error-as-an-experimental-variable-how-to-quantify-it-and-use-it-to-optimize-cytometry-panels\/#primaryimage","url":"https:\/\/immunostep.com\/wp-content\/uploads\/2026\/02\/Spreading-error-as-an-experimental-variable.png","contentUrl":"https:\/\/immunostep.com\/wp-content\/uploads\/2026\/02\/Spreading-error-as-an-experimental-variable.png","width":900,"height":600,"caption":"Spreading error as an experimental variable"},{"@type":"BreadcrumbList","@id":"https:\/\/immunostep.com\/2026\/02\/25\/spreading-error-as-an-experimental-variable-how-to-quantify-it-and-use-it-to-optimize-cytometry-panels\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https:\/\/immunostep.com\/es\/"},{"@type":"ListItem","position":2,"name":"Spreading error as an experimental variable: How to quantify it and use it to optimize cytometry panels"}]},{"@type":"WebSite","@id":"https:\/\/immunostep.com\/#website","url":"https:\/\/immunostep.com\/","name":"Immunostep Biotech","description":"Innovating to deliver high-performance technology for Research and Diagnosis","publisher":{"@id":"https:\/\/immunostep.com\/#organization"},"potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/immunostep.com\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"es"},{"@type":"Organization","@id":"https:\/\/immunostep.com\/#organization","name":"Immunostep Biotech","url":"https:\/\/immunostep.com\/","logo":{"@type":"ImageObject","inLanguage":"es","@id":"https:\/\/immunostep.com\/#\/schema\/logo\/image\/","url":"https:\/\/immunostep.com\/wp-content\/uploads\/2021\/10\/logo-web-color.png","contentUrl":"https:\/\/immunostep.com\/wp-content\/uploads\/2021\/10\/logo-web-color.png","width":1299,"height":591,"caption":"Immunostep Biotech"},"image":{"@id":"https:\/\/immunostep.com\/#\/schema\/logo\/image\/"},"sameAs":["https:\/\/www.facebook.com\/immunostepsl\/","https:\/\/x.com\/Immunostep","https:\/\/www.linkedin.com\/company\/immunostepsl\/"]},{"@type":"Person","@id":"https:\/\/immunostep.com\/#\/schema\/person\/6f7086a7900eb41588a2465bcae5f427","name":"\u00c1ngela Cabestrero","image":{"@type":"ImageObject","inLanguage":"es","@id":"https:\/\/immunostep.com\/#\/schema\/person\/image\/","url":"https:\/\/secure.gravatar.com\/avatar\/378033e78b9b0300f6f50aeac830c5cf?s=96&d=mm&r=g","contentUrl":"https:\/\/secure.gravatar.com\/avatar\/378033e78b9b0300f6f50aeac830c5cf?s=96&d=mm&r=g","caption":"\u00c1ngela Cabestrero"},"url":"https:\/\/immunostep.com\/es\/author\/acabestrero\/"}]}},"_links":{"self":[{"href":"https:\/\/immunostep.com\/es\/wp-json\/wp\/v2\/posts\/39048"}],"collection":[{"href":"https:\/\/immunostep.com\/es\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/immunostep.com\/es\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/immunostep.com\/es\/wp-json\/wp\/v2\/users\/225"}],"replies":[{"embeddable":true,"href":"https:\/\/immunostep.com\/es\/wp-json\/wp\/v2\/comments?post=39048"}],"version-history":[{"count":1,"href":"https:\/\/immunostep.com\/es\/wp-json\/wp\/v2\/posts\/39048\/revisions"}],"predecessor-version":[{"id":39053,"href":"https:\/\/immunostep.com\/es\/wp-json\/wp\/v2\/posts\/39048\/revisions\/39053"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/immunostep.com\/es\/wp-json\/wp\/v2\/media\/39051"}],"wp:attachment":[{"href":"https:\/\/immunostep.com\/es\/wp-json\/wp\/v2\/media?parent=39048"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/immunostep.com\/es\/wp-json\/wp\/v2\/categories?post=39048"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/immunostep.com\/es\/wp-json\/wp\/v2\/tags?post=39048"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}