A citation-based method for searching scientific literature

Oliver Stegle, Sarah A Teichmann, John C Marioni. Nat Rev Genet 2015
Times Cited: 518







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



Times Cited
  Times     Co-cited
Similarity


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
40

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
36

Integrating single-cell transcriptomic data across different conditions, technologies, and species.
Andrew Butler, Paul Hoffman, Peter Smibert, Efthymia Papalexi, Rahul Satija. Nat Biotechnol 2018
33

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
29

Spatial reconstruction of single-cell gene expression data.
Rahul Satija, Jeffrey A Farrell, David Gennert, Alexander F Schier, Aviv Regev. Nat Biotechnol 2015
27

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
25

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
25

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
24

Challenges in unsupervised clustering of single-cell RNA-seq data.
Vladimir Yu Kiselev, Tallulah S Andrews, Martin Hemberg. Nat Rev Genet 2019
190
23

Bayesian approach to single-cell differential expression analysis.
Peter V Kharchenko, Lev Silberstein, David T Scadden. Nat Methods 2014
529
20

SC3: consensus clustering of single-cell RNA-seq data.
Vladimir Yu Kiselev, Kristina Kirschner, Michael T Schaub, Tallulah Andrews, Andrew Yiu, Tamir Chandra, Kedar N Natarajan, Wolf Reik, Mauricio Barahona, Anthony R Green,[...]. Nat Methods 2017
441
20

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
428
20

Quantitative single-cell RNA-seq with unique molecular identifiers.
Saiful Islam, Amit Zeisel, Simon Joost, Gioele La Manno, Pawel Zajac, Maria Kasper, Peter Lönnerberg, Sten Linnarsson. Nat Methods 2014
580
19

SAVER: gene expression recovery for single-cell RNA sequencing.
Mo Huang, Jingshu Wang, Eduardo Torre, Hannah Dueck, Sydney Shaffer, Roberto Bonasio, John I Murray, Arjun Raj, Mingyao Li, Nancy R Zhang. Nat Methods 2018
162
18

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
502
17

Accounting for technical noise in single-cell RNA-seq experiments.
Philip Brennecke, Simon Anders, Jong Kyoung Kim, Aleksandra A Kołodziejczyk, Xiuwei Zhang, Valentina Proserpio, Bianka Baying, Vladimir Benes, Sarah A Teichmann, John C Marioni,[...]. Nat Methods 2013
488
17

The Human Cell Atlas.
Aviv Regev, Sarah A Teichmann, Eric S Lander, Ido Amit, Christophe Benoist, Ewan Birney, Bernd Bodenmiller, Peter Campbell, Piero Carninci, Menna Clatworthy,[...]. Elife 2017
632
17

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
328
17

Design and computational analysis of single-cell RNA-sequencing experiments.
Rhonda Bacher, Christina Kendziorski. Genome Biol 2016
200
16

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
359
16

Integrative single-cell analysis.
Tim Stuart, Rahul Satija. Nat Rev Genet 2019
285
16

Brain structure. Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq.
Amit Zeisel, Ana B Muñoz-Manchado, Simone Codeluppi, Peter Lönnerberg, Gioele La Manno, Anna Juréus, Sueli Marques, Hermany Munguba, Liqun He, Christer Betsholtz,[...]. Science 2015
15

SCANPY: large-scale single-cell gene expression data analysis.
F Alexander Wolf, Philipp Angerer, Fabian J Theis. Genome Biol 2018
623
15

Normalizing single-cell RNA sequencing data: challenges and opportunities.
Catalina A Vallejos, Davide Risso, Antonio Scialdone, Sandrine Dudoit, John C Marioni. Nat Methods 2017
151
15

Single-cell RNA sequencing technologies and bioinformatics pipelines.
Byungjin Hwang, Ji Hyun Lee, Duhee Bang. Exp Mol Med 2018
351
15

Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma.
Anoop P Patel, Itay Tirosh, John J Trombetta, Alex K Shalek, Shawn M Gillespie, Hiroaki Wakimoto, Daniel P Cahill, Brian V Nahed, William T Curry, Robert L Martuza,[...]. Science 2014
15

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
535
15

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
376
15


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


Massively parallel single-cell RNA-seq for marker-free decomposition of tissues into cell types.
Diego Adhemar Jaitin, Ephraim Kenigsberg, Hadas Keren-Shaul, Naama Elefant, Franziska Paul, Irina Zaretsky, Alexander Mildner, Nadav Cohen, Steffen Jung, Amos Tanay,[...]. Science 2014
852
14


Deep generative modeling for single-cell transcriptomics.
Romain Lopez, Jeffrey Regier, Michael B Cole, Michael I Jordan, Nir Yosef. Nat Methods 2018
200
14

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
13

The technology and biology of single-cell RNA sequencing.
Aleksandra A Kolodziejczyk, Jong Kyoung Kim, Valentine Svensson, John C Marioni, Sarah A Teichmann. Mol Cell 2015
439
13

Computational analysis of cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals hidden subpopulations of cells.
Florian Buettner, Kedar N Natarajan, F Paolo Casale, Valentina Proserpio, Antonio Scialdone, Fabian J Theis, Sarah A Teichmann, John C Marioni, Oliver Stegle. Nat Biotechnol 2015
550
13

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
628
13


Single-Cell Multi-omic Integration Compares and Contrasts Features of Brain Cell Identity.
Joshua D Welch, Velina Kozareva, Ashley Ferreira, Charles Vanderburg, Carly Martin, Evan Z Macosko. Cell 2019
187
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
738
13


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
350
12

Missing data and technical variability in single-cell RNA-sequencing experiments.
Stephanie C Hicks, F William Townes, Mingxiang Teng, Rafael A Irizarry. Biostatistics 2018
133
12

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
961
12

CEL-Seq: single-cell RNA-Seq by multiplexed linear amplification.
Tamar Hashimshony, Florian Wagner, Noa Sher, Itai Yanai. Cell Rep 2012
595
12

Single-Cell Map of Diverse Immune Phenotypes in the Breast Tumor Microenvironment.
Elham Azizi, Ambrose J Carr, George Plitas, Andrew E Cornish, Catherine Konopacki, Sandhya Prabhakaran, Juozas Nainys, Kenmin Wu, Vaidotas Kiseliovas, Manu Setty,[...]. Cell 2018
466
12

A Single-Cell Transcriptomic Map of the Human and Mouse Pancreas Reveals Inter- and Intra-cell Population Structure.
Maayan Baron, Adrian Veres, Samuel L Wolock, Aubrey L Faust, Renaud Gaujoux, Amedeo Vetere, Jennifer Hyoje Ryu, Bridget K Wagner, Shai S Shen-Orr, Allon M Klein,[...]. Cell Syst 2016
367
12

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
575
11



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.