A citation-based method for searching scientific literature

Shijie C Zheng, Charles E Breeze, Stephan Beck, Andrew E Teschendorff. Nat Methods 2018
Times Cited: 66







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



Times Cited
  Times     Co-cited
Similarity


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
45

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
31


A comparison of reference-based algorithms for correcting cell-type heterogeneity in Epigenome-Wide Association Studies.
Andrew E Teschendorff, Charles E Breeze, Shijie C Zheng, Stephan Beck. BMC Bioinformatics 2017
133
27

Robust enumeration of cell subsets from tissue expression profiles.
Aaron M Newman, Chih Long Liu, Michael R Green, Andrew J Gentles, Weiguo Feng, Yue Xu, Chuong D Hoang, Maximilian Diehn, Ash A Alizadeh. Nat Methods 2015
22

Epigenome-wide association data implicate DNA methylation as an intermediary of genetic risk in rheumatoid arthritis.
Yun Liu, Martin J Aryee, Leonid Padyukov, M Daniele Fallin, Espen Hesselberg, Arni Runarsson, Lovisa Reinius, Nathalie Acevedo, Margaret Taub, Marcus Ronninger,[...]. Nat Biotechnol 2013
599
22

Cell type-specific gene expression differences in complex tissues.
Shai S Shen-Orr, Robert Tibshirani, Purvesh Khatri, Dale L Bodian, Frank Staedtler, Nicholas M Perry, Trevor Hastie, Minnie M Sarwal, Mark M Davis, Atul J Butte. Nat Methods 2010
306
19

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
18

Integrative analysis of 111 reference human epigenomes.
Anshul Kundaje, Wouter Meuleman, Jason Ernst, Misha Bilenky, Angela Yen, Alireza Heravi-Moussavi, Pouya Kheradpour, Zhizhuo Zhang, Jianrong Wang, Michael J Ziller,[...]. Nature 2015
18

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
813
18


A novel cell-type deconvolution algorithm reveals substantial contamination by immune cells in saliva, buccal and cervix.
Shijie C Zheng, Amy P Webster, Danyue Dong, Andy Feber, David G Graham, Roisin Sullivan, Sarah Jevons, Laurence B Lovat, Stephan Beck, Martin Widschwendter,[...]. Epigenomics 2018
61
16


Epigenome-wide association study of body mass index, and the adverse outcomes of adiposity.
Simone Wahl, Alexander Drong, Benjamin Lehne, Marie Loh, William R Scott, Sonja Kunze, Pei-Chien Tsai, Janina S Ried, Weihua Zhang, Youwen Yang,[...]. Nature 2017
437
12

Genome-wide methylation profiles reveal quantitative views of human aging rates.
Gregory Hannum, Justin Guinney, Ling Zhao, Li Zhang, Guy Hughes, SriniVas Sadda, Brandy Klotzle, Marina Bibikova, Jian-Bing Fan, Yuan Gao,[...]. Mol Cell 2013
12

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
12

Epigenome-wide association studies for common human diseases.
Vardhman K Rakyan, Thomas A Down, David J Balding, Stephan Beck. Nat Rev Genet 2011
775
12

Reference-free cell mixture adjustments in analysis of DNA methylation data.
Eugene Andres Houseman, John Molitor, Carmen J Marsit. Bioinformatics 2014
274
10

Measuring cell-type specific differential methylation in human brain tissue.
Carolina M Montaño, Rafael A Irizarry, Walter E Kaufmann, Konrad Talbot, Raquel E Gur, Andrew P Feinberg, Margaret A Taub. Genome Biol 2013
67
10

Improving cell mixture deconvolution by identifying optimal DNA methylation libraries (IDOL).
Devin C Koestler, Meaghan J Jones, Joseph Usset, Brock C Christensen, Rondi A Butler, Michael S Kobor, John K Wiencke, Karl T Kelsey. BMC Bioinformatics 2016
66
10

Dissecting differential signals in high-throughput data from complex tissues.
Ziyi Li, Zhijin Wu, Peng Jin, Hao Wu. Bioinformatics 2019
14
50

missMethyl: an R package for analyzing data from Illumina's HumanMethylation450 platform.
Belinda Phipson, Jovana Maksimovic, Alicia Oshlack. Bioinformatics 2016
291
10

Statistical and integrative system-level analysis of DNA methylation data.
Andrew E Teschendorff, Caroline L Relton. Nat Rev Genet 2018
129
10

Epigenome-wide association studies without the need for cell-type composition.
James Zou, Christoph Lippert, David Heckerman, Martin Aryee, Jennifer Listgarten. Nat Methods 2014
134
9


Cell-type deconvolution from DNA methylation: a review of recent applications.
Alexander J Titus, Rachel M Gallimore, Lucas A Salas, Brock C Christensen. Hum Mol Genet 2017
68
9

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
877
9

An optimized library for reference-based deconvolution of whole-blood biospecimens assayed using the Illumina HumanMethylationEPIC BeadArray.
Lucas A Salas, Devin C Koestler, Rondi A Butler, Helen M Hansen, John K Wiencke, Karl T Kelsey, Brock C Christensen. Genome Biol 2018
97
9

Differential DNA methylation in purified human blood cells: implications for cell lineage and studies on disease susceptibility.
Lovisa E Reinius, Nathalie Acevedo, Maaike Joerink, Göran Pershagen, Sven-Erik Dahlén, Dario Greco, Cilla Söderhäll, Annika Scheynius, Juha Kere. PLoS One 2012
655
9

Determining cell type abundance and expression from bulk tissues with digital cytometry.
Aaron M Newman, Chloé B Steen, Chih Long Liu, Andrew J Gentles, Aadel A Chaudhuri, Florian Scherer, Michael S Khodadoust, Mohammad S Esfahani, Bogdan A Luca, David Steiner,[...]. Nat Biotechnol 2019
729
9

Cell-type-specific resolution epigenetics without the need for cell sorting or single-cell biology.
Elior Rahmani, Regev Schweiger, Brooke Rhead, Lindsey A Criswell, Lisa F Barcellos, Eleazar Eskin, Saharon Rosset, Sriram Sankararaman, Eran Halperin. Nat Commun 2019
28
21

Correlation of an epigenetic mitotic clock with cancer risk.
Zhen Yang, Andrew Wong, Diana Kuh, Dirk S Paul, Vardhman K Rakyan, R David Leslie, Shijie C Zheng, Martin Widschwendter, Stephan Beck, Andrew E Teschendorff. Genome Biol 2016
97
9

RaMWAS: fast methylome-wide association study pipeline for enrichment platforms.
Andrey A Shabalin, Mohammad W Hattab, Shaunna L Clark, Robin F Chan, Gaurav Kumar, Karolina A Aberg, Edwin J C G van den Oord. Bioinformatics 2018
27
22

Adjusting batch effects in microarray expression data using empirical Bayes methods.
W Evan Johnson, Cheng Li, Ariel Rabinovic. Biostatistics 2007
7

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
7

ChAMP: 450k Chip Analysis Methylation Pipeline.
Tiffany J Morris, Lee M Butcher, Andrew Feber, Andrew E Teschendorff, Ankur R Chakravarthy, Tomasz K Wojdacz, Stephan Beck. Bioinformatics 2014
451
7

Low-level processing of Illumina Infinium DNA Methylation BeadArrays.
Timothy J Triche, Daniel J Weisenberger, David Van Den Berg, Peter W Laird, Kimberly D Siegmund. Nucleic Acids Res 2013
365
7

Preprocessing, normalization and integration of the Illumina HumanMethylationEPIC array with minfi.
Jean-Philippe Fortin, Timothy J Triche, Kasper D Hansen. Bioinformatics 2017
268
7

Bulk tissue cell type deconvolution with multi-subject single-cell expression reference.
Xuran Wang, Jihwan Park, Katalin Susztak, Nancy R Zhang, Mingyao Li. Nat Commun 2019
204
7

Single-cell genome-wide bisulfite sequencing for assessing epigenetic heterogeneity.
Sébastien A Smallwood, Heather J Lee, Christof Angermueller, Felix Krueger, Heba Saadeh, Julian Peat, Simon R Andrews, Oliver Stegle, Wolf Reik, Gavin Kelsey. Nat Methods 2014
563
7

High density DNA methylation array with single CpG site resolution.
Marina Bibikova, Bret Barnes, Chan Tsan, Vincent Ho, Brandy Klotzle, Jennie M Le, David Delano, Lu Zhang, Gary P Schroth, Kevin L Gunderson,[...]. Genomics 2011
7

eFORGE: A Tool for Identifying Cell Type-Specific Signal in Epigenomic Data.
Charles E Breeze, Dirk S Paul, Jenny van Dongen, Lee M Butcher, John C Ambrose, James E Barrett, Robert Lowe, Vardhman K Rakyan, Valentina Iotchkova, Mattia Frontini,[...]. Cell Rep 2016
65
7




Correcting for cell-type heterogeneity in epigenome-wide association studies: revisiting previous analyses.
Shijie C Zheng, Stephan Beck, Andrew E Jaffe, Devin C Koestler, Kasper D Hansen, Andres E Houseman, Rafael A Irizarry, Andrew E Teschendorff. Nat Methods 2017
47
10

Critical evaluation of the Illumina MethylationEPIC BeadChip microarray for whole-genome DNA methylation profiling.
Ruth Pidsley, Elena Zotenko, Timothy J Peters, Mitchell G Lawrence, Gail P Risbridger, Peter Molloy, Susan Van Djik, Beverly Muhlhausler, Clare Stirzaker, Susan J Clark. Genome Biol 2016
457
7

A cell-type deconvolution meta-analysis of whole blood EWAS reveals lineage-specific smoking-associated DNA methylation changes.
Chenglong You, Sijie Wu, Shijie C Zheng, Tianyu Zhu, Han Jing, Ken Flagg, Guangyu Wang, Li Jin, Sijia Wang, Andrew E Teschendorff. Nat Commun 2020
11
45


Reference-free deconvolution of DNA methylation data and mediation by cell composition effects.
E Andres Houseman, Molly L Kile, David C Christiani, Tan A Ince, Karl T Kelsey, Carmen J Marsit. BMC Bioinformatics 2016
118
6


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.