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List of co-cited articles
437 articles co-cited >1



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
59

Integrating single-cell transcriptomic data across different conditions, technologies, and species.
Andrew Butler, Paul Hoffman, Peter Smibert, Efthymia Papalexi, Rahul Satija. Nat Biotechnol 2018
59

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
21

Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets.
Evan Z Macosko, Anindita Basu, Rahul Satija, James Nemesh, Karthik Shekhar, Melissa Goldman, Itay Tirosh, Allison R Bialas, Nolan Kamitaki, Emily M Martersteck,[...]. Cell 2015
20

MAST: a flexible statistical framework for assessing transcriptional changes and characterizing heterogeneity in single-cell RNA sequencing data.
Greg Finak, Andrew McDavid, Masanao Yajima, Jingyuan Deng, Vivian Gersuk, Alex K Shalek, Chloe K Slichter, Hannah W Miller, M Juliana McElrath, Martin Prlic,[...]. Genome Biol 2015
559
17

Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles.
Aravind Subramanian, Pablo Tamayo, Vamsi K Mootha, Sayan Mukherjee, Benjamin L Ebert, Michael A Gillette, Amanda Paulovich, Scott L Pomeroy, Todd R Golub, Eric S Lander,[...]. Proc Natl Acad Sci U S A 2005
16

Massively parallel digital transcriptional profiling of single cells.
Grace X Y Zheng, Jessica M Terry, Phillip Belgrader, Paul Ryvkin, Zachary W Bent, Ryan Wilson, Solongo B Ziraldo, Tobias D Wheeler, Geoff P McDermott, Junjie Zhu,[...]. Nat Commun 2017
14

Reference-based analysis of lung single-cell sequencing reveals a transitional profibrotic macrophage.
Dvir Aran, Agnieszka P Looney, Leqian Liu, Esther Wu, Valerie Fong, Austin Hsu, Suzanna Chak, Ram P Naikawadi, Paul J Wolters, Adam R Abate,[...]. Nat Immunol 2019
324
14

Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2.
Michael I Love, Wolfgang Huber, Simon Anders. Genome Biol 2014
14

RNA velocity of single cells.
Gioele La Manno, Ruslan Soldatov, Amit Zeisel, Emelie Braun, Hannah Hochgerner, Viktor Petukhov, Katja Lidschreiber, Maria E Kastriti, Peter Lönnerberg, Alessandro Furlan,[...]. Nature 2018
562
13

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
696
12

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
316
12

clusterProfiler: an R package for comparing biological themes among gene clusters.
Guangchuang Yu, Li-Gen Wang, Yanyan Han, Qing-Yu He. OMICS 2012
12

limma powers differential expression analyses for RNA-sequencing and microarray studies.
Matthew E Ritchie, Belinda Phipson, Di Wu, Yifang Hu, Charity W Law, Wei Shi, Gordon K Smyth. Nucleic Acids Res 2015
10

edgeR: a Bioconductor package for differential expression analysis of digital gene expression data.
Mark D Robinson, Davis J McCarthy, Gordon K Smyth. Bioinformatics 2010
9

Current best practices in single-cell RNA-seq analysis: a tutorial.
Malte D Luecken, Fabian J Theis. Mol Syst Biol 2019
255
9

Comparative Analysis of Single-Cell RNA Sequencing Methods.
Christoph Ziegenhain, Beate Vieth, Swati Parekh, Björn Reinius, Amy Guillaumet-Adkins, Martha Smets, Heinrich Leonhardt, Holger Heyn, Ines Hellmann, Wolfgang Enard. Mol Cell 2017
488
9

Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells.
Allon M Klein, Linas Mazutis, Ilke Akartuna, Naren Tallapragada, Adrian Veres, Victor Li, Leonid Peshkin, David A Weitz, Marc W Kirschner. Cell 2015
9

The single-cell transcriptional landscape of mammalian organogenesis.
Junyue Cao, Malte Spielmann, Xiaojie Qiu, Xingfan Huang, Daniel M Ibrahim, Andrew J Hill, Fan Zhang, Stefan Mundlos, Lena Christiansen, Frank J Steemers,[...]. Nature 2019
365
9

Molecular Architecture of the Mouse Nervous System.
Amit Zeisel, Hannah Hochgerner, Peter Lönnerberg, Anna Johnsson, Fatima Memic, Job van der Zwan, Martin Häring, Emelie Braun, Lars E Borm, Gioele La Manno,[...]. Cell 2018
618
9

DoubletFinder: Doublet Detection in Single-Cell RNA Sequencing Data Using Artificial Nearest Neighbors.
Christopher S McGinnis, Lyndsay M Murrow, Zev J Gartner. Cell Syst 2019
171
9

Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq.
Itay Tirosh, Benjamin Izar, Sanjay M Prakadan, Marc H Wadsworth, Daniel Treacy, John J Trombetta, Asaf Rotem, Christopher Rodman, Christine Lian, George Murphy,[...]. Science 2016
9

SCnorm: robust normalization of single-cell RNA-seq data.
Rhonda Bacher, Li-Fang Chu, Ning Leng, Audrey P Gasch, James A Thomson, Ron M Stewart, Michael Newton, Christina Kendziorski. Nat Methods 2017
119
8

Slingshot: cell lineage and pseudotime inference for single-cell transcriptomics.
Kelly Street, Davide Risso, Russell B Fletcher, Diya Das, John Ngai, Nir Yosef, Elizabeth Purdom, Sandrine Dudoit. BMC Genomics 2018
291
8


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
413
8

Spatial reconstruction of single-cell gene expression data.
Rahul Satija, Jeffrey A Farrell, David Gennert, Alexander F Schier, Aviv Regev. Nat Biotechnol 2015
8

SCANPY: large-scale single-cell gene expression data analysis.
F Alexander Wolf, Philipp Angerer, Fabian J Theis. Genome Biol 2018
592
8

Pooling across cells to normalize single-cell RNA sequencing data with many zero counts.
Aaron T L Lun, Karsten Bach, John C Marioni. Genome Biol 2016
345
7

SCENIC: single-cell regulatory network inference and clustering.
Sara Aibar, Carmen Bravo González-Blas, Thomas Moerman, Vân Anh Huynh-Thu, Hana Imrichova, Gert Hulselmans, Florian Rambow, Jean-Christophe Marine, Pierre Geurts, Jan Aerts,[...]. Nat Methods 2017
524
7

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
7


Near-optimal probabilistic RNA-seq quantification.
Nicolas L Bray, Harold Pimentel, Páll Melsted, Lior Pachter. Nat Biotechnol 2016
7


The Sequence Alignment/Map format and SAMtools.
Heng Li, Bob Handsaker, Alec Wysoker, Tim Fennell, Jue Ruan, Nils Homer, Gabor Marth, Goncalo Abecasis, Richard Durbin. Bioinformatics 2009
7

Diffusion pseudotime robustly reconstructs lineage branching.
Laleh Haghverdi, Maren Büttner, F Alexander Wolf, Florian Buettner, Fabian J Theis. Nat Methods 2016
334
6

Classification of low quality cells from single-cell RNA-seq data.
Tomislav Ilicic, Jong Kyoung Kim, Aleksandra A Kolodziejczyk, Frederik Otzen Bagger, Davis James McCarthy, John C Marioni, Sarah A Teichmann. Genome Biol 2016
209
6

Reversed graph embedding resolves complex single-cell trajectories.
Xiaojie Qiu, Qi Mao, Ying Tang, Li Wang, Raghav Chawla, Hannah A Pliner, Cole Trapnell. Nat Methods 2017
664
6

Recovering Gene Interactions from Single-Cell Data Using Data Diffusion.
David van Dijk, Roshan Sharma, Juozas Nainys, Kristina Yim, Pooja Kathail, Ambrose J Carr, Cassandra Burdziak, Kevin R Moon, Christine L Chaffer, Diwakar Pattabiraman,[...]. Cell 2018
321
6

Single-cell profiling of the developing mouse brain and spinal cord with split-pool barcoding.
Alexander B Rosenberg, Charles M Roco, Richard A Muscat, Anna Kuchina, Paul Sample, Zizhen Yao, Lucas T Graybuck, David J Peeler, Sumit Mukherjee, Wei Chen,[...]. Science 2018
333
6

Smart-seq2 for sensitive full-length transcriptome profiling in single cells.
Simone Picelli, Åsa K Björklund, Omid R Faridani, Sven Sagasser, Gösta Winberg, Rickard Sandberg. Nat Methods 2013
944
6

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
353
6

Visualization and analysis of gene expression in tissue sections by spatial transcriptomics.
Patrik L Ståhl, Fredrik Salmén, Sanja Vickovic, Anna Lundmark, José Fernández Navarro, Jens Magnusson, Stefania Giacomello, Michaela Asp, Jakub O Westholm, Mikael Huss,[...]. Science 2016
500
6

Model-based analysis of ChIP-Seq (MACS).
Yong Zhang, Tao Liu, Clifford A Meyer, Jérôme Eeckhoute, David S Johnson, Bradley E Bernstein, Chad Nusbaum, Richard M Myers, Myles Brown, Wei Li,[...]. Genome Biol 2008
6

Fast gapped-read alignment with Bowtie 2.
Ben Langmead, Steven L Salzberg. Nat Methods 2012
6


Cytoscape: a software environment for integrated models of biomolecular interaction networks.
Paul Shannon, Andrew Markiel, Owen Ozier, Nitin S Baliga, Jonathan T Wang, Daniel Ramage, Nada Amin, Benno Schwikowski, Trey Ideker. Genome Res 2003
6

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. Nat Methods 2017
604
6

mRNA-Seq whole-transcriptome analysis of a single cell.
Fuchou Tang, Catalin Barbacioru, Yangzhou Wang, Ellen Nordman, Clarence Lee, Nanlan Xu, Xiaohui Wang, John Bodeau, Brian B Tuch, Asim Siddiqui,[...]. Nat Methods 2009
5

Full-length RNA-seq from single cells using Smart-seq2.
Simone Picelli, Omid R Faridani, Asa K Björklund, Gösta Winberg, Sven Sagasser, Rickard Sandberg. Nat Protoc 2014
5


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.