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1
Batch effects in single-cell RNA-sequencing data are corrected by matching mutual nearest neighbors
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Batch effects in single-cell RNA-sequencing data are corrected by matching mutual nearest neighbors

Haghverdi, Laleh ; Lun, Aaron T L ; Morgan, Michael D ; Marioni, John C

Nature biotechnology, 2018-06, Vol.36 (5), p.421-427 [Periódico revisado por pares]

United States: Nature Publishing Group

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2
Computational and analytical challenges in single-cell transcriptomics
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Computational and analytical challenges in single-cell transcriptomics

Stegle, Oliver ; Teichmann, Sarah A ; Marioni, John C

Nature reviews. Genetics, 2015-03, Vol.16 (3), p.133-145 [Periódico revisado por pares]

England: Nature Publishing Group

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3
Multi‐Omics Factor Analysis—a framework for unsupervised integration of multi‐omics data sets
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Multi‐Omics Factor Analysis—a framework for unsupervised integration of multi‐omics data sets

Argelaguet, Ricard ; Velten, Britta ; Arnol, Damien ; Dietrich, Sascha ; Zenz, Thorsten ; Marioni, John C ; Buettner, Florian ; Huber, Wolfgang ; Stegle, Oliver

Molecular systems biology, 2018-06, Vol.14 (6), p.e8124-n/a [Periódico revisado por pares]

England: EMBO Press

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4
Stabilized mosaic single-cell data integration using unshared features
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Stabilized mosaic single-cell data integration using unshared features

Ghazanfar, Shila ; Guibentif, Carolina ; Marioni, John C

Nature biotechnology, 2024-02, Vol.42 (2), p.284-292 [Periódico revisado por pares]

United States: Nature Publishing Group

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5
BASiCS: Bayesian Analysis of Single-Cell Sequencing Data
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BASiCS: Bayesian Analysis of Single-Cell Sequencing Data

Vallejos, Catalina A ; Marioni, John C ; Richardson, Sylvia Morris, Quaid

PLoS computational biology, 2015-06, Vol.11 (6), p.e1004333-e1004333 [Periódico revisado por pares]

United States: Public Library of Science

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6
EmptyDrops: distinguishing cells from empty droplets in droplet-based single-cell RNA sequencing data
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EmptyDrops: distinguishing cells from empty droplets in droplet-based single-cell RNA sequencing data

Lun, Aaron T L ; Riesenfeld, Samantha ; Andrews, Tallulah ; Dao, The Phuong ; Gomes, Tomas ; Marioni, John C

Genome Biology, 2019-03, Vol.20 (1), p.63-63, Article 63 [Periódico revisado por pares]

England: BioMed Central

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7
Using single‐cell genomics to understand developmental processes and cell fate decisions
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Using single‐cell genomics to understand developmental processes and cell fate decisions

Griffiths, Jonathan A ; Scialdone, Antonio ; Marioni, John C

Molecular systems biology, 2018-04, Vol.14 (4), p.e8046-n/a [Periódico revisado por pares]

England: EMBO Press

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8
Computational analysis of cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals hidden subpopulations of cells
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Computational analysis of cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals hidden subpopulations of cells

Buettner, Florian ; Natarajan, Kedar N ; Casale, F Paolo ; Proserpio, Valentina ; Scialdone, Antonio ; Theis, Fabian J ; Teichmann, Sarah A ; Marioni, John C ; Stegle, Oliver

Nature biotechnology, 2015-02, Vol.33 (2), p.155-160 [Periódico revisado por pares]

United States: Nature Publishing Group

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9
Classification of low quality cells from single-cell RNA-seq data
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Classification of low quality cells from single-cell RNA-seq data

Ilicic, Tomislav ; Kim, Jong Kyoung ; Kolodziejczyk, Aleksandra A ; Bagger, Frederik Otzen ; McCarthy, Davis James ; Marioni, John C ; Teichmann, Sarah A

Genome Biology, 2016-02, Vol.17 (1), p.29-29, Article 29 [Periódico revisado por pares]

England: BioMed Central

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10
High-throughput spatial mapping of single-cell RNA-seq data to tissue of origin
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High-throughput spatial mapping of single-cell RNA-seq data to tissue of origin

Achim, Kaia ; Pettit, Jean-Baptiste ; Saraiva, Luis R ; Gavriouchkina, Daria ; Larsson, Tomas ; Arendt, Detlev ; Marioni, John C

Nature biotechnology, 2015-05, Vol.33 (5), p.503-509 [Periódico revisado por pares]

United States: Nature Publishing Group

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