Joshua D Welch, Velina Kozareva, Ashley Ferreira, Charles Vanderburg, Carly Martin, Evan Z Macosko. Cell 2019
Times Cited: 187
Times Cited: 187
Times Cited
Times Co-cited
Similarity
Comprehensive Integration of Single-Cell Data.
Tim Stuart, Andrew Butler, Paul Hoffman, Christoph Hafemeister, Efthymia Papalexi, William M Mauck, Yuhan Hao, Marlon Stoeckius, Peter Smibert, Rahul Satija. Cell 2019
Tim Stuart, Andrew Butler, Paul Hoffman, Christoph Hafemeister, Efthymia Papalexi, William M Mauck, Yuhan Hao, Marlon Stoeckius, Peter Smibert, Rahul Satija. Cell 2019
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Fast, sensitive and accurate integration of single-cell data with Harmony.
Ilya Korsunsky, Nghia Millard, Jean Fan, Kamil Slowikowski, Fan Zhang, Kevin Wei, Yuriy Baglaenko, Michael Brenner, Po-Ru Loh, Soumya Raychaudhuri. Nat Methods 2019
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Integrating single-cell transcriptomic data across different conditions, technologies, and species.
Andrew Butler, Paul Hoffman, Peter Smibert, Efthymia Papalexi, Rahul Satija. Nat Biotechnol 2018
Andrew Butler, Paul Hoffman, Peter Smibert, Efthymia Papalexi, Rahul Satija. Nat Biotechnol 2018
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Batch effects in single-cell RNA-sequencing data are corrected by matching mutual nearest neighbors.
Laleh Haghverdi, Aaron T L Lun, Michael D Morgan, John C Marioni. Nat Biotechnol 2018
Laleh Haghverdi, Aaron T L Lun, Michael D Morgan, John C Marioni. Nat Biotechnol 2018
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A benchmark of batch-effect correction methods for single-cell RNA sequencing data.
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Hoa Thi Nhu Tran, Kok Siong Ang, Marion Chevrier, Xiaomeng Zhang, Nicole Yee Shin Lee, Michelle Goh, Jinmiao Chen. Genome Biol 2020
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Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets.
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Efficient integration of heterogeneous single-cell transcriptomes using Scanorama.
Brian Hie, Bryan Bryson, Bonnie Berger. Nat Biotechnol 2019
Brian Hie, Bryan Bryson, Bonnie Berger. Nat Biotechnol 2019
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Slide-seq: A scalable technology for measuring genome-wide expression at high spatial resolution.
Samuel G Rodriques, Robert R Stickels, Aleksandrina Goeva, Carly A Martin, Evan Murray, Charles R Vanderburg, Joshua Welch, Linlin M Chen, Fei Chen, Evan Z Macosko. Science 2019
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Massively parallel digital transcriptional profiling of single cells.
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Molecular, spatial, and functional single-cell profiling of the hypothalamic preoptic region.
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RNA velocity of single cells.
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scmap: projection of single-cell RNA-seq data across data sets.
Vladimir Yu Kiselev, Andrew Yiu, Martin Hemberg. Nat Methods 2018
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Current best practices in single-cell RNA-seq analysis: a tutorial.
Malte D Luecken, Fabian J Theis. Mol Syst Biol 2019
Malte D Luecken, Fabian J Theis. Mol Syst Biol 2019
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Spatial reconstruction of single-cell gene expression data.
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Three-dimensional intact-tissue sequencing of single-cell transcriptional states.
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Simultaneous epitope and transcriptome measurement in single cells.
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The single-cell transcriptional landscape of mammalian organogenesis.
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F Alexander Wolf, Philipp Angerer, Fabian J Theis. Genome Biol 2018
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Joint analysis of heterogeneous single-cell RNA-seq dataset collections.
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Visualization and analysis of gene expression in tissue sections by spatial transcriptomics.
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Transcriptome-scale super-resolved imaging in tissues by RNA seqFISH.
Chee-Huat Linus Eng, Michael Lawson, Qian Zhu, Ruben Dries, Noushin Koulena, Yodai Takei, Jina Yun, Christopher Cronin, Christoph Karp, Guo-Cheng Yuan,[...]. Nature 2019
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Deep generative modeling for single-cell transcriptomics.
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Comprehensive single-cell transcriptional profiling of a multicellular organism.
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Dimensionality reduction for visualizing single-cell data using UMAP.
Etienne Becht, Leland McInnes, John Healy, Charles-Antoine Dutertre, Immanuel W H Kwok, Lai Guan Ng, Florent Ginhoux, Evan W Newell. Nat Biotechnol 2018
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The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells.
Cole Trapnell, Davide Cacchiarelli, Jonna Grimsby, Prapti Pokharel, Shuqiang Li, Michael Morse, Niall J Lennon, Kenneth J Livak, Tarjei S Mikkelsen, John L Rinn. Nat Biotechnol 2014
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SC3: consensus clustering of single-cell RNA-seq data.
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A Single-Cell Transcriptomic Map of the Human and Mouse Pancreas Reveals Inter- and Intra-cell Population Structure.
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Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells.
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Integrative single-cell analysis of transcriptional and epigenetic states in the human adult brain.
Blue B Lake, Song Chen, Brandon C Sos, Jean Fan, Gwendolyn E Kaeser, Yun C Yung, Thu E Duong, Derek Gao, Jerold Chun, Peter V Kharchenko,[...]. Nat Biotechnol 2018
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mRNA-Seq whole-transcriptome analysis of a single cell.
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Single-cell profiling of the developing mouse brain and spinal cord with split-pool barcoding.
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Molecular Diversity and Specializations among the Cells of the Adult Mouse Brain.
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A Single-Cell Atlas of In Vivo Mammalian Chromatin Accessibility.
Darren A Cusanovich, Andrew J Hill, Delasa Aghamirzaie, Riza M Daza, Hannah A Pliner, Joel B Berletch, Galina N Filippova, Xingfan Huang, Lena Christiansen, William S DeWitt,[...]. Cell 2018
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STAR: ultrafast universal RNA-seq aligner.
Alexander Dobin, Carrie A Davis, Felix Schlesinger, Jorg Drenkow, Chris Zaleski, Sonali Jha, Philippe Batut, Mark Chaisson, Thomas R Gingeras. Bioinformatics 2013
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Multi-Omics Factor Analysis-a framework for unsupervised integration of multi-omics data sets.
Ricard Argelaguet, Britta Velten, Damien Arnol, Sascha Dietrich, Thorsten Zenz, John C Marioni, Florian Buettner, Wolfgang Huber, Oliver Stegle. Mol Syst Biol 2018
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Parallel single-cell sequencing links transcriptional and epigenetic heterogeneity.
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Challenges in unsupervised clustering of single-cell RNA-seq data.
Vladimir Yu Kiselev, Tallulah S Andrews, Martin Hemberg. Nat Rev Genet 2019
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Conserved cell types with divergent features in human versus mouse cortex.
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A comparison of single-cell trajectory inference methods.
Wouter Saelens, Robrecht Cannoodt, Helena Todorov, Yvan Saeys. Nat Biotechnol 2019
Wouter Saelens, Robrecht Cannoodt, Helena Todorov, Yvan Saeys. Nat Biotechnol 2019
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chromVAR: inferring transcription-factor-associated accessibility from single-cell epigenomic data.
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Joint profiling of chromatin accessibility and gene expression in thousands of single cells.
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Single-cell chromatin accessibility reveals principles of regulatory variation.
Jason D Buenrostro, Beijing Wu, Ulrike M Litzenburger, Dave Ruff, Michael L Gonzales, Michael P Snyder, Howard Y Chang, William J Greenleaf. Nature 2015
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Slingshot: cell lineage and pseudotime inference for single-cell transcriptomics.
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Generalizing RNA velocity to transient cell states through dynamical modeling.
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Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2.
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Co-cited is the co-citation frequency, indicating how many articles cite the article together with the query article. Similarity is the co-citation as percentage of the times cited of the query article or the article in the search results, whichever is the lowest. These numbers are calculated for the last 100 citations when articles are cited more than 100 times.