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CITEMO(XMBD): A flexible single-cell multimodal omics analysis framework to reveal the heterogeneity of immune cells

Simultaneous measurement of multiple modalities in single-cell analysis, represented by CITE-seq, is a promising approach to link transcriptional changes to cellular phenotype and function, requiring new computational methods to define cellular subtypes and states based on multiple data types. Here,...

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Autores principales: Hu, Huan, Liu, Ruiqi, Zhao, Chunlin, Lu, Yuer, Xiong, Yichun, Chen, Lingling, Jin, Jun, Ma, Yunlong, Su, Jianzhong, Yu, Zhengquan, Cheng, Feng, Ye, Fangfu, Liu, Liyu, Zhao, Qi, Shuai, Jianwei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8824218/
https://www.ncbi.nlm.nih.gov/pubmed/35130112
http://dx.doi.org/10.1080/15476286.2022.2027151
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author Hu, Huan
Liu, Ruiqi
Zhao, Chunlin
Lu, Yuer
Xiong, Yichun
Chen, Lingling
Jin, Jun
Ma, Yunlong
Su, Jianzhong
Yu, Zhengquan
Cheng, Feng
Ye, Fangfu
Liu, Liyu
Zhao, Qi
Shuai, Jianwei
author_facet Hu, Huan
Liu, Ruiqi
Zhao, Chunlin
Lu, Yuer
Xiong, Yichun
Chen, Lingling
Jin, Jun
Ma, Yunlong
Su, Jianzhong
Yu, Zhengquan
Cheng, Feng
Ye, Fangfu
Liu, Liyu
Zhao, Qi
Shuai, Jianwei
author_sort Hu, Huan
collection PubMed
description Simultaneous measurement of multiple modalities in single-cell analysis, represented by CITE-seq, is a promising approach to link transcriptional changes to cellular phenotype and function, requiring new computational methods to define cellular subtypes and states based on multiple data types. Here, we design a flexible single-cell multimodal analysis framework, called CITEMO, to integrate the transcriptome and antibody-derived tags (ADT) data to capture cell heterogeneity from the multi omics perspective. CITEMO uses Principal Component Analysis (PCA) to obtain a low-dimensional representation of the transcriptome and ADT, respectively, and then employs PCA again to integrate these low-dimensional multimodal data for downstream analysis. To investigate the effectiveness of the CITEMO framework, we apply CITEMO to analyse the cell subtypes of Cord Blood Mononuclear Cells (CBMC) samples. Results show that the CITEMO framework can comprehensively analyse single-cell multimodal samples and accurately identify cell subtypes. Besides, we find some specific immune cells that co-express multiple ADT markers. To better describe the co-expression phenomenon, we introduce the co-expression entropy to measure the heterogeneous distribution of the ADT combinations. To further validate the robustness of the CITEMO framework, we analyse Human Bone Marrow Cell (HBMC) samples and identify different states of the same cell type. CITEMO has an excellent performance in identifying cell subtypes and states for multimodal omics data. We suggest that the flexible design idea of CITEMO can be an inspiration for other single-cell multimodal tasks. The complete source code and dataset of the CITEMO framework can be obtained from https://github.com/studentiz/CITEMO.
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spelling pubmed-88242182022-02-09 CITEMO(XMBD): A flexible single-cell multimodal omics analysis framework to reveal the heterogeneity of immune cells Hu, Huan Liu, Ruiqi Zhao, Chunlin Lu, Yuer Xiong, Yichun Chen, Lingling Jin, Jun Ma, Yunlong Su, Jianzhong Yu, Zhengquan Cheng, Feng Ye, Fangfu Liu, Liyu Zhao, Qi Shuai, Jianwei RNA Biol Research Paper Simultaneous measurement of multiple modalities in single-cell analysis, represented by CITE-seq, is a promising approach to link transcriptional changes to cellular phenotype and function, requiring new computational methods to define cellular subtypes and states based on multiple data types. Here, we design a flexible single-cell multimodal analysis framework, called CITEMO, to integrate the transcriptome and antibody-derived tags (ADT) data to capture cell heterogeneity from the multi omics perspective. CITEMO uses Principal Component Analysis (PCA) to obtain a low-dimensional representation of the transcriptome and ADT, respectively, and then employs PCA again to integrate these low-dimensional multimodal data for downstream analysis. To investigate the effectiveness of the CITEMO framework, we apply CITEMO to analyse the cell subtypes of Cord Blood Mononuclear Cells (CBMC) samples. Results show that the CITEMO framework can comprehensively analyse single-cell multimodal samples and accurately identify cell subtypes. Besides, we find some specific immune cells that co-express multiple ADT markers. To better describe the co-expression phenomenon, we introduce the co-expression entropy to measure the heterogeneous distribution of the ADT combinations. To further validate the robustness of the CITEMO framework, we analyse Human Bone Marrow Cell (HBMC) samples and identify different states of the same cell type. CITEMO has an excellent performance in identifying cell subtypes and states for multimodal omics data. We suggest that the flexible design idea of CITEMO can be an inspiration for other single-cell multimodal tasks. The complete source code and dataset of the CITEMO framework can be obtained from https://github.com/studentiz/CITEMO. Taylor & Francis 2022-02-07 /pmc/articles/PMC8824218/ /pubmed/35130112 http://dx.doi.org/10.1080/15476286.2022.2027151 Text en © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Paper
Hu, Huan
Liu, Ruiqi
Zhao, Chunlin
Lu, Yuer
Xiong, Yichun
Chen, Lingling
Jin, Jun
Ma, Yunlong
Su, Jianzhong
Yu, Zhengquan
Cheng, Feng
Ye, Fangfu
Liu, Liyu
Zhao, Qi
Shuai, Jianwei
CITEMO(XMBD): A flexible single-cell multimodal omics analysis framework to reveal the heterogeneity of immune cells
title CITEMO(XMBD): A flexible single-cell multimodal omics analysis framework to reveal the heterogeneity of immune cells
title_full CITEMO(XMBD): A flexible single-cell multimodal omics analysis framework to reveal the heterogeneity of immune cells
title_fullStr CITEMO(XMBD): A flexible single-cell multimodal omics analysis framework to reveal the heterogeneity of immune cells
title_full_unstemmed CITEMO(XMBD): A flexible single-cell multimodal omics analysis framework to reveal the heterogeneity of immune cells
title_short CITEMO(XMBD): A flexible single-cell multimodal omics analysis framework to reveal the heterogeneity of immune cells
title_sort citemo(xmbd): a flexible single-cell multimodal omics analysis framework to reveal the heterogeneity of immune cells
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8824218/
https://www.ncbi.nlm.nih.gov/pubmed/35130112
http://dx.doi.org/10.1080/15476286.2022.2027151
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