A citation-based method for searching scientific literature

Catalina A Vallejos, Davide Risso, Antonio Scialdone, Sandrine Dudoit, John C Marioni. Nat Methods 2017
Times Cited: 151







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



Times Cited
  Times     Co-cited
Similarity


Integrating single-cell transcriptomic data across different conditions, technologies, and species.
Andrew Butler, Paul Hoffman, Peter Smibert, Efthymia Papalexi, Rahul Satija. Nat Biotechnol 2018
39

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
37

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
36

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
35

Bayesian approach to single-cell differential expression analysis.
Peter V Kharchenko, Lev Silberstein, David T Scadden. Nat Methods 2014
529
33

Computational and analytical challenges in single-cell transcriptomics.
Oliver Stegle, Sarah A Teichmann, John C Marioni. Nat Rev Genet 2015
518
30

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
30

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
30

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
123
29

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
27

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
27

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
26

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
26

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
25

Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2.
Michael I Love, Wolfgang Huber, Simon Anders. Genome Biol 2014
24

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
212
22


A general and flexible method for signal extraction from single-cell RNA-seq data.
Davide Risso, Fanny Perraudeau, Svetlana Gribkova, Sandrine Dudoit, Jean-Philippe Vert. Nat Commun 2018
174
22

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
22

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
21

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
21

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

BASiCS: Bayesian Analysis of Single-Cell Sequencing Data.
Catalina A Vallejos, John C Marioni, Sylvia Richardson. PLoS Comput Biol 2015
128
19


Differential expression analysis for sequence count data.
Simon Anders, Wolfgang Huber. Genome Biol 2010
19

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
19

Scater: pre-processing, quality control, normalization and visualization of single-cell RNA-seq data in R.
Davis J McCarthy, Kieran R Campbell, Aaron T L Lun, Quin F Wills. Bioinformatics 2017
382
18


SCANPY: large-scale single-cell gene expression data analysis.
F Alexander Wolf, Philipp Angerer, Fabian J Theis. Genome Biol 2018
623
18

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
18

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
17


Spatial reconstruction of single-cell gene expression data.
Rahul Satija, Jeffrey A Farrell, David Gennert, Alexander F Schier, Aviv Regev. Nat Biotechnol 2015
17

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

Batch effects and the effective design of single-cell gene expression studies.
Po-Yuan Tung, John D Blischak, Chiaowen Joyce Hsiao, David A Knowles, Jonathan E Burnett, Jonathan K Pritchard, Yoav Gilad. Sci Rep 2017
123
16

Characterization of the single-cell transcriptional landscape by highly multiplex RNA-seq.
Saiful Islam, Una Kjällquist, Annalena Moliner, Pawel Zajac, Jian-Bing Fan, Peter Lönnerberg, Sten Linnarsson. Genome Res 2011
474
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
16


scmap: projection of single-cell RNA-seq data across data sets.
Vladimir Yu Kiselev, Andrew Yiu, Martin Hemberg. Nat Methods 2018
165
16


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
15

A comparison of single-cell trajectory inference methods.
Wouter Saelens, Robrecht Cannoodt, Helena Todorov, Yvan Saeys. Nat Biotechnol 2019
269
15

Challenges in unsupervised clustering of single-cell RNA-seq data.
Vladimir Yu Kiselev, Tallulah S Andrews, Martin Hemberg. Nat Rev Genet 2019
190
15

Validation of noise models for single-cell transcriptomics.
Dominic Grün, Lennart Kester, Alexander van Oudenaarden. Nat Methods 2014
321
14

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
14

Visualization and analysis of single-cell RNA-seq data by kernel-based similarity learning.
Bo Wang, Junjie Zhu, Emma Pierson, Daniele Ramazzotti, Serafim Batzoglou. Nat Methods 2017
189
14

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
14

Splatter: simulation of single-cell RNA sequencing data.
Luke Zappia, Belinda Phipson, Alicia Oshlack. Genome Biol 2017
174
14

A systematic performance evaluation of clustering methods for single-cell RNA-seq data.
Angelo Duò, Mark D Robinson, Charlotte Soneson. F1000Res 2018
79
17


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.