Simultaneous epitope and transcriptome measurement in single cells.
Marlon Stoeckius,Christoph Hafemeister,William Stephenson,Brian Houck-Loomis,Pratip K. Chattopadhyay,Harold Swerdlow,Rahul Satija,Peter Smibert +7 more
TLDR
In this article, a method called cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) is proposed, in which oligonucleotide-labeled antibodies are used to integrate cellular protein and transcriptome measurements into an efficient, single-cell readout.Abstract:
High-throughput single-cell RNA sequencing has transformed our understanding of complex cell populations, but it does not provide phenotypic information such as cell-surface protein levels. Here, we describe cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq), a method in which oligonucleotide-labeled antibodies are used to integrate cellular protein and transcriptome measurements into an efficient, single-cell readout. CITE-seq is compatible with existing single-cell sequencing approaches and scales readily with throughput increases.read more
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Journal ArticleDOI
Comprehensive Integration of Single-Cell Data.
Tim Stuart,Andrew Butler,Paul J. Hoffman,Christoph Hafemeister,Efthymia Papalexi,William M. Mauck,Yuhan Hao,Marlon Stoeckius,Peter Smibert,Rahul Satija +9 more
TL;DR: A strategy to "anchor" diverse datasets together, enabling us to integrate single-cell measurements not only across scRNA-seq technologies, but also across different modalities.
Journal ArticleDOI
Integrated analysis of multimodal single-cell data
Yuhan Hao,Stephanie Hao,Erica Andersen-Nissen,William M. Mauck,Shiwei Zheng,Andrew Butler,Maddie Jane Lee,Aaron J. Wilk,Charlotte A. Darby,Michael Zager,Paul Hoffman,Marlon Stoeckius,Efthymia Papalexi,Eleni P. Mimitou,Jaison Jain,Avi Srivastava,Tim Stuart,Lamar M. Fleming,Bertrand Z. Yeung,Angela J. Rogers,Juliana M. McElrath,Catherine A. Blish,Raphael Gottardo,Peter Smibert,Rahul Satija +24 more
TL;DR: Weighted-nearest neighbor analysis as mentioned in this paper is an unsupervised framework to learn the relative utility of each data type in each cell, enabling an integrative analysis of multiple modalities.
Posted ContentDOI
Integrated analysis of multimodal single-cell data
Yuhan Hao,Stephanie Hao,Erica Andersen-Nissen,William M. Mauck,Shiwei Zheng,Andrew Butler,Maddie Jane Lee,Aaron J. Wilk,Charlotte A. Darby,Michael Zagar,Paul Hoffman,Marlon Stoeckius,Efthymia Papalexi,Eleni P. Mimitou,Jaison Jain,Avi Srivastava,Tim Stuart,Lamar Ballweber Fleming,Bertrand Z. Yeung,Angela J. Rogers,Juliana M. McElrath,Catherine A. Blish,Raphael Gottardo,Peter Smibert,Rahul Satija +24 more
TL;DR: ‘weighted-nearest neighbor’ analysis is introduced, an unsupervised framework to learn the relative utility of each data type in each cell, enabling an integrative analysis of multiple modalities.
Posted ContentDOI
Comprehensive integration of single cell data
Tim Stuart,Andrew Butler,Paul J. Hoffman,Christoph Hafemeister,Efthymia Papalexi,William M. Mauck,Marlon Stoeckius,Peter Smibert,Rahul Satija +8 more
TL;DR: This work presents a strategy for comprehensive integration of single cell data, including the assembly of harmonized references, and the transfer of information across datasets, and demonstrates how anchoring can harmonize in-situ gene expression and scRNA-seq datasets.
Journal ArticleDOI
Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression
TL;DR: It is proposed that the Pearson residuals from “regularized negative binomial regression,” where cellular sequencing depth is utilized as a covariate in a generalized linear model, successfully remove the influence of technical characteristics from downstream analyses while preserving biological heterogeneity.
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