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Adjacent Cell Marker Lateral Spillover Compensation and Reinforcement for Multiplexed Images
Multiplex imaging technologies are now routinely capable of measuring more than 40 antibody-labeled parameters in single cells. However, lateral spillage of signals in densely packed tissues presents an obstacle to the assignment of high-dimensional spatial features to individual cells for accurate...
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Published in: | Frontiers in immunology 2021-07, Vol.12, p.652631-652631 |
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creator | Bai, Yunhao Zhu, Bokai Rovira-Clave, Xavier Chen, Han Markovic, Maxim Chan, Chi Ngai Su, Tung-Hung McIlwain, David R Estes, Jacob D Keren, Leeat Nolan, Garry P Jiang, Sizun |
description | Multiplex imaging technologies are now routinely capable of measuring more than 40 antibody-labeled parameters in single cells. However, lateral spillage of signals in densely packed tissues presents an obstacle to the assignment of high-dimensional spatial features to individual cells for accurate cell-type annotation. We devised a method to correct for lateral spillage of cell surface markers between adjacent cells termed REinforcement Dynamic Spillover EliminAtion (REDSEA). The use of REDSEA decreased contaminating signals from neighboring cells. It improved the recovery of marker signals across both isotopic (i.e., Multiplexed Ion Beam Imaging) and immunofluorescent (i.e., Cyclic Immunofluorescence) multiplexed images resulting in a marked improvement in cell-type classification. |
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However, lateral spillage of signals in densely packed tissues presents an obstacle to the assignment of high-dimensional spatial features to individual cells for accurate cell-type annotation. We devised a method to correct for lateral spillage of cell surface markers between adjacent cells termed REinforcement Dynamic Spillover EliminAtion (REDSEA). The use of REDSEA decreased contaminating signals from neighboring cells. It improved the recovery of marker signals across both isotopic (i.e., Multiplexed Ion Beam Imaging) and immunofluorescent (i.e., Cyclic Immunofluorescence) multiplexed images resulting in a marked improvement in cell-type classification.</description><subject>Animals</subject><subject>Biomarkers</subject><subject>cell annotation</subject><subject>Cell Lineage</subject><subject>Fluorescent Antibody Technique - methods</subject><subject>image correction</subject><subject>Image Processing, Computer-Assisted</subject><subject>Immunology</subject><subject>Molecular Imaging - methods</subject><subject>Molecular Imaging - standards</subject><subject>multiplexed tissue imaging</subject><subject>Reproducibility of Results</subject><subject>Sensitivity and Specificity</subject><subject>signal spillover</subject><subject>Signal-To-Noise Ratio</subject><subject>Single-Cell Analysis - methods</subject><subject>Single-Cell Analysis - standards</subject><subject>single-cell biology</subject><subject>spatial proteomics</subject><issn>1664-3224</issn><issn>1664-3224</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>DOA</sourceid><recordid>eNpVkU1v1DAQhi0EolXpD-CCcuSyiz_ixLkgVSsKK22FBD0iWRN7vHhx4mAnFfx7vN1Stb54NJ55Zvy-hLxldC2E6j44PwzLmlPO1o3kjWAvyDlrmnolOK9fPonPyGXOB1pO3Qkh5GtyJmreScHbc_Ljyh7A4DhXGwyhuoH0C1O1gxkThOr75EOIdyWzicOEY4bZx7GC0Vbf0I8uJoPDsblE1c0SZj8F_IO22g6wx_yGvHIQMl4-3Bfk9vrT7ebLavf183ZztVuZupHzyhnuaqEoojPSMHTUIvaqlR0q6JvausZgo1xvZN9a01uqhLFKsRaELT-6INsT1kY46Cn5AdJfHcHr-0RMew1p9iagBi5Y3zvq0NnaGFACjHCthLapyzAsrI8n1rT0A9qjMkWIZ9DnL6P_qffxTiuuupZ2BfD-AZDi7wXzrAefTdEWRoxL1lxKyajshCyl7FRqUsw5oXscw6g-eqzvPdZHj_XJ49Lz7ul-jx3_HRX_ACHnp6M</recordid><startdate>20210705</startdate><enddate>20210705</enddate><creator>Bai, Yunhao</creator><creator>Zhu, Bokai</creator><creator>Rovira-Clave, Xavier</creator><creator>Chen, Han</creator><creator>Markovic, Maxim</creator><creator>Chan, Chi Ngai</creator><creator>Su, Tung-Hung</creator><creator>McIlwain, David R</creator><creator>Estes, Jacob D</creator><creator>Keren, Leeat</creator><creator>Nolan, Garry P</creator><creator>Jiang, Sizun</creator><general>Frontiers Media S.A</general><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><scope>DOA</scope></search><sort><creationdate>20210705</creationdate><title>Adjacent Cell Marker Lateral Spillover Compensation and Reinforcement for Multiplexed Images</title><author>Bai, Yunhao ; Zhu, Bokai ; Rovira-Clave, Xavier ; Chen, Han ; Markovic, Maxim ; Chan, Chi Ngai ; Su, Tung-Hung ; McIlwain, David R ; Estes, Jacob D ; Keren, Leeat ; Nolan, Garry P ; Jiang, Sizun</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c465t-fc2f4380eefc5c1ef0deeb8759e8ab64df6ce68fbc5b7dcbd083cd8817a3d333</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Animals</topic><topic>Biomarkers</topic><topic>cell annotation</topic><topic>Cell Lineage</topic><topic>Fluorescent Antibody Technique - methods</topic><topic>image correction</topic><topic>Image Processing, Computer-Assisted</topic><topic>Immunology</topic><topic>Molecular Imaging - methods</topic><topic>Molecular Imaging - standards</topic><topic>multiplexed tissue imaging</topic><topic>Reproducibility of Results</topic><topic>Sensitivity and Specificity</topic><topic>signal spillover</topic><topic>Signal-To-Noise Ratio</topic><topic>Single-Cell Analysis - methods</topic><topic>Single-Cell Analysis - standards</topic><topic>single-cell biology</topic><topic>spatial proteomics</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Bai, Yunhao</creatorcontrib><creatorcontrib>Zhu, Bokai</creatorcontrib><creatorcontrib>Rovira-Clave, Xavier</creatorcontrib><creatorcontrib>Chen, Han</creatorcontrib><creatorcontrib>Markovic, Maxim</creatorcontrib><creatorcontrib>Chan, Chi Ngai</creatorcontrib><creatorcontrib>Su, Tung-Hung</creatorcontrib><creatorcontrib>McIlwain, David R</creatorcontrib><creatorcontrib>Estes, Jacob D</creatorcontrib><creatorcontrib>Keren, Leeat</creatorcontrib><creatorcontrib>Nolan, Garry P</creatorcontrib><creatorcontrib>Jiang, Sizun</creatorcontrib><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><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Frontiers in immunology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Bai, Yunhao</au><au>Zhu, Bokai</au><au>Rovira-Clave, Xavier</au><au>Chen, Han</au><au>Markovic, Maxim</au><au>Chan, Chi Ngai</au><au>Su, Tung-Hung</au><au>McIlwain, David R</au><au>Estes, Jacob D</au><au>Keren, Leeat</au><au>Nolan, Garry P</au><au>Jiang, Sizun</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Adjacent Cell Marker Lateral Spillover Compensation and Reinforcement for Multiplexed Images</atitle><jtitle>Frontiers in immunology</jtitle><addtitle>Front Immunol</addtitle><date>2021-07-05</date><risdate>2021</risdate><volume>12</volume><spage>652631</spage><epage>652631</epage><pages>652631-652631</pages><issn>1664-3224</issn><eissn>1664-3224</eissn><abstract>Multiplex imaging technologies are now routinely capable of measuring more than 40 antibody-labeled parameters in single cells. 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subjects | Animals Biomarkers cell annotation Cell Lineage Fluorescent Antibody Technique - methods image correction Image Processing, Computer-Assisted Immunology Molecular Imaging - methods Molecular Imaging - standards multiplexed tissue imaging Reproducibility of Results Sensitivity and Specificity signal spillover Signal-To-Noise Ratio Single-Cell Analysis - methods Single-Cell Analysis - standards single-cell biology spatial proteomics |
title | Adjacent Cell Marker Lateral Spillover Compensation and Reinforcement for Multiplexed Images |
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