A citation-based method for searching scientific literature

Jeffrey T Leek, John D Storey. PLoS Genet 2007
Times Cited: 924







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



Times Cited
  Times     Co-cited
Similarity


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
29

Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2.
Michael I Love, Wolfgang Huber, Simon Anders. Genome Biol 2014
25

Adjusting batch effects in microarray expression data using empirical Bayes methods.
W Evan Johnson, Cheng Li, Ariel Rabinovic. Biostatistics 2007
22

The sva package for removing batch effects and other unwanted variation in high-throughput experiments.
Jeffrey T Leek, W Evan Johnson, Hilary S Parker, Andrew E Jaffe, John D Storey. Bioinformatics 2012
22

edgeR: a Bioconductor package for differential expression analysis of digital gene expression data.
Mark D Robinson, Davis J McCarthy, Gordon K Smyth. Bioinformatics 2010
18

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
15

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
14

Tackling the widespread and critical impact of batch effects in high-throughput data.
Jeffrey T Leek, Robert B Scharpf, Héctor Corrada Bravo, David Simcha, Benjamin Langmead, W Evan Johnson, Donald Geman, Keith Baggerly, Rafael A Irizarry. Nat Rev Genet 2010
947
11



voom: Precision weights unlock linear model analysis tools for RNA-seq read counts.
Charity W Law, Yunshun Chen, Wei Shi, Gordon K Smyth. Genome Biol 2014
11

Using control genes to correct for unwanted variation in microarray data.
Johann A Gagnon-Bartsch, Terence P Speed. Biostatistics 2012
211
11

DNA methylation arrays as surrogate measures of cell mixture distribution.
Eugene Andres Houseman, William P Accomando, Devin C Koestler, Brock C Christensen, Carmen J Marsit, Heather H Nelson, John K Wiencke, Karl T Kelsey. BMC Bioinformatics 2012
9

Comparison of Beta-value and M-value methods for quantifying methylation levels by microarray analysis.
Pan Du, Xiao Zhang, Chiang-Ching Huang, Nadereh Jafari, Warren A Kibbe, Lifang Hou, Simon M Lin. BMC Bioinformatics 2010
981
9



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

clusterProfiler: an R package for comparing biological themes among gene clusters.
Guangchuang Yu, Li-Gen Wang, Yanyan Han, Qing-Yu He. OMICS 2012
7


Genetic effects on gene expression across human tissues.
Alexis Battle, Christopher D Brown, Barbara E Engelhardt, Stephen B Montgomery. Nature 2017
6

Molecular signatures database (MSigDB) 3.0.
Arthur Liberzon, Aravind Subramanian, Reid Pinchback, Helga Thorvaldsdóttir, Pablo Tamayo, Jill P Mesirov. Bioinformatics 2011
6


Normalization of RNA-seq data using factor analysis of control genes or samples.
Davide Risso, John Ngai, Terence P Speed, Sandrine Dudoit. Nat Biotechnol 2014
675
6

Statistical significance for genomewide studies.
John D Storey, Robert Tibshirani. Proc Natl Acad Sci U S A 2003
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

WGCNA: an R package for weighted correlation network analysis.
Peter Langfelder, Steve Horvath. BMC Bioinformatics 2008
6

De novo identification of differentially methylated regions in the human genome.
Timothy J Peters, Michael J Buckley, Aaron L Statham, Ruth Pidsley, Katherine Samaras, Reginald V Lord, Susan J Clark, Peter L Molloy. Epigenetics Chromatin 2015
329
5

Minfi: a flexible and comprehensive Bioconductor package for the analysis of Infinium DNA methylation microarrays.
Martin J Aryee, Andrew E Jaffe, Hector Corrada-Bravo, Christine Ladd-Acosta, Andrew P Feinberg, Kasper D Hansen, Rafael A Irizarry. Bioinformatics 2014
5

Enrichr: a comprehensive gene set enrichment analysis web server 2016 update.
Maxim V Kuleshov, Matthew R Jones, Andrew D Rouillard, Nicolas F Fernandez, Qiaonan Duan, Zichen Wang, Simon Koplev, Sherry L Jenkins, Kathleen M Jagodnik, Alexander Lachmann,[...]. Nucleic Acids Res 2016
5

Discovery of cross-reactive probes and polymorphic CpGs in the Illumina Infinium HumanMethylation450 microarray.
Yi-an Chen, Mathieu Lemire, Sanaa Choufani, Darci T Butcher, Daria Grafodatskaya, Brent W Zanke, Steven Gallinger, Thomas J Hudson, Rosanna Weksberg. Epigenetics 2013
809
5



The Molecular Signatures Database (MSigDB) hallmark gene set collection.
Arthur Liberzon, Chet Birger, Helga Thorvaldsdóttir, Mahmoud Ghandi, Jill P Mesirov, Pablo Tamayo. Cell Syst 2015
5

A beta-mixture quantile normalization method for correcting probe design bias in Illumina Infinium 450 k DNA methylation data.
Andrew E Teschendorff, Francesco Marabita, Matthias Lechner, Thomas Bartlett, Jesper Tegner, David Gomez-Cabrero, Stephan Beck. Bioinformatics 2013
732
5

Trimmomatic: a flexible trimmer for Illumina sequence data.
Anthony M Bolger, Marc Lohse, Bjoern Usadel. Bioinformatics 2014
5

HTSeq--a Python framework to work with high-throughput sequencing data.
Simon Anders, Paul Theodor Pyl, Wolfgang Huber. Bioinformatics 2015
5

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
775
5

Variance stabilization applied to microarray data calibration and to the quantification of differential expression.
Wolfgang Huber, Anja von Heydebreck, Holger Sültmann, Annemarie Poustka, Martin Vingron. Bioinformatics 2002
5

Orchestrating high-throughput genomic analysis with Bioconductor.
Wolfgang Huber, Vincent J Carey, Robert Gentleman, Simon Anders, Marc Carlson, Benilton S Carvalho, Hector Corrada Bravo, Sean Davis, Laurent Gatto, Thomas Girke,[...]. Nat Methods 2015
5

Integrating single-cell transcriptomic data across different conditions, technologies, and species.
Andrew Butler, Paul Hoffman, Peter Smibert, Efthymia Papalexi, Rahul Satija. Nat Biotechnol 2018
5

Why Batch Effects Matter in Omics Data, and How to Avoid Them.
Wilson Wen Bin Goh, Wei Wang, Limsoon Wong. Trends Biotechnol 2017
123
5

A framework for oligonucleotide microarray preprocessing.
Benilton S Carvalho, Rafael A Irizarry. Bioinformatics 2010
801
5

Gene ontology: tool for the unification of biology. The Gene Ontology Consortium.
M Ashburner, C A Ball, J A Blake, D Botstein, H Butler, J M Cherry, A P Davis, K Dolinski, S S Dwight, J T Eppig,[...]. Nat Genet 2000
5


Removing batch effects in analysis of expression microarray data: an evaluation of six batch adjustment methods.
Chao Chen, Kay Grennan, Judith Badner, Dandan Zhang, Elliot Gershon, Li Jin, Chunyu Liu. PLoS One 2011
236
4

A general framework for multiple testing dependence.
Jeffrey T Leek, John D Storey. Proc Natl Acad Sci U S A 2008
157
4

Near-optimal probabilistic RNA-seq quantification.
Nicolas L Bray, Harold Pimentel, Páll Melsted, Lior Pachter. Nat Biotechnol 2016
4

A gene-based association method for mapping traits using reference transcriptome data.
Eric R Gamazon, Heather E Wheeler, Kaanan P Shah, Sahar V Mozaffari, Keston Aquino-Michaels, Robert J Carroll, Anne E Eyler, Joshua C Denny, Dan L Nicolae, Nancy J Cox,[...]. Nat Genet 2015
592
4

Salmon provides fast and bias-aware quantification of transcript expression.
Rob Patro, Geet Duggal, Michael I Love, Rafael A Irizarry, Carl Kingsford. Nat Methods 2017
4


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.