ggplot2: Elegant Graphics for Data Analysis

lmerTest Package: Tests in Linear Mixed Effects Models

Kuznetsova, A., Brockhoff, P. B., & Christensen, R. H. B. (2017) · Journal of Statistical Software · doi:10.18637/jss.v082.i13 · Cited by 24,346

Welcome to the tidyverse

Wickham, H., Averick, M., Bryan, J., Chang, W., McGowan, L., François, R., Grolemund, G., Hayes, A., Henry, L., Hester, J., et al. (2019) · Journal of Open Source Software · doi:10.21105/joss.01686 · Cited by 22,138

phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data

McMurdie, P. J., & Holmes, S. (2013) · PLoS ONE · doi:10.1371/journal.pone.0061217 · Cited by 21,942

Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks

Trapnell, C., Roberts, A., Goff, L. A., Pertea, G. M., Kim, D., Kelley, D. R., Pimentel, H., Salzberg, S. L., Rinn, J. L., & Pachter, L. S. (2012) · Nature Protocols · doi:10.1038/nprot.2012.016 · Cited by 12,145

CBTRUS Statistical Report: Primary Brain and Central Nervous System Tumors Diagnosed in the United States in 2006-2010

Ostrom, Q. T., Gittleman, H. R., Farah, P., Ondracek, A., Chen, Y., Wolinsky, Y., Stroup, N. E., Kruchko, C., & Barnholtz‐Sloan, J. S. (2013) · Neuro-Oncology · doi:10.1093/neuonc/not151 · Cited by 12,063

Genome sequence-based species delimitation with confidence intervals and improved distance functions

Meier‐Kolthoff, J. P., Auch, A. F., Klenk, H., & Göker, M. (2013) · BMC Bioinformatics · doi:10.1186/1471-2105-14-60 · Cited by 6,838

From FastQ data to high confidence variant calls: the Genome Analysis Toolkit best practices pipeline

Van der Auwera, G. A., Carneiro, M. O., Hartl, C., Poplin, R., del Angel, G., Levy‐Moonshine, A., Jordan, T., Shakir, K., Roazen, D., Thibault, J., et al. (2013) · Current Protocols in Bioinformatics · doi:10.1002/0471250953.bi1110s43 · Cited by 6,687

BUSCO Update: Novel and Streamlined Workflows along with Broader and Deeper Phylogenetic Coverage for Scoring of Eukaryotic, Prokaryotic, and Viral Genomes

Manni, M., Berkeley, M. R., Seppey, M., Simão, F. A., & Zdobnov, E. M. (2021) · Molecular Biology and Evolution · doi:10.1093/molbev/msab199 · Cited by 6,187

ggtree : an r package for visualization and annotation of phylogenetic trees with their covariates and other associated data

Yu, G., Smith, D. K., Zhu, H., Guan, Y., & Lam, T. T. (2016) · Methods in Ecology and Evolution · doi:10.1111/2041-210x.12628 · Cited by 4,821

Topology of the human and mouse m6A RNA methylomes revealed by m6A-seq

Dominissini, D., Moshitch-Moshkovitz, S., Schwartz, S., Salmon-Divon, M., Ungar, L., Osenberg, S., Cesarkas, K., Jacob-Hirsch, J., Amariglio, N., Kupiec, M., et al. (2012) · Nature · doi:10.1038/nature11112 · Cited by 4,884

UpSetR: an R package for the visualization of intersecting sets and their properties

Conway, J. R., Lex, A., & Gehlenborg, N. (2017) · Bioinformatics · doi:10.1093/bioinformatics/btx364 · Cited by 3,586

Imbalanced Host Response to SARS-CoV-2 Drives Development of COVID-19

Blanco-Melo, D., Nilsson-Payant, B. E., Liu, W.-C., Uhl, S., Hoagland, D., Møller, R., Jordan, T. X., Oishi, K., Panis, M., Sachs, D., et al. (2020) · Cell · doi:10.1016/j.cell.2020.04.026 · Cited by 4,222

ClustVis: a web tool for visualizing clustering of multivariate data using Principal Component Analysis and heatmap

Metsalu, T., & Vilo, J. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv468 · Cited by 3,770

Multi-omics of the gut microbial ecosystem in inflammatory bowel diseases

Lloyd-Price, J., Arze, C., Ananthakrishnan, A. N., Schirmer, M., Avila-Pacheco, J., Poon, T. W., Andrews, E., Ajami, N. J., Bonham, K. S., Brislawn, C. J., et al. (2019) · Nature · doi:10.1038/s41586-019-1237-9 · Cited by 3,143

D³ Data-Driven Documents

Bostock, M., Ogievetsky, V., & Heer, J. (2011) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2011.185 · Cited by 3,165

Waste Not, Want Not: Why Rarefying Microbiome Data Is Inadmissible

McMurdie, P. J., & Holmes, S. (2014) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003531 · Cited by 3,034

ggeffects: Tidy Data Frames of Marginal Effects from Regression Models

Lüdecke, D. (2018) · The Journal of Open Source Software · doi:10.21105/joss.00772 · Cited by 2,742

Detection of a SARS-CoV-2 variant of concern in South Africa

Tegally, H., Wilkinson, E., Giovanetti, M., Iranzadeh, A., Fonseca, V., Giandhari, J., Doolabh, D., Pillay, S., San, E. J., Msomi, N., et al. (2021) · Nature · doi:10.1038/s41586-021-03402-9 · Cited by 2,510

CSF-1R inhibition alters macrophage polarization and blocks glioma progression

Pyonteck, S. M., Akkari, L., Schuhmacher, A. J., Bowman, R. L., Sevenich, L., Quail, D. F., Olson, O. C., Quick, M. L., Huse, J. T., Teijeiro, V., et al. (2013) · Nature Medicine · doi:10.1038/nm.3337 · Cited by 2,463

A review of statistically-based landslide susceptibility models

Reichenbach, P., Rossi, M., Malamud, B. D., Mihir, M., & Guzzetti, F. (2018) · Earth-Science Reviews · doi:10.1016/j.earscirev.2018.03.001 · Cited by 2,466

unmarked : An R Package for Fitting Hierarchical Models of Wildlife Occurrence and Abundance

Fiske, I., & Chandler, R. B. (2011) · Journal of Statistical Software · doi:10.18637/jss.v043.i10 · Cited by 2,373

Heatmapper: web-enabled heat mapping for all

Babicki, S., Arndt, D., Marcu, A., Liang, Y., Grant, J. R., Maciejewski, A., & Wishart, D. S. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw419 · Cited by 2,306

BUSCO: Assessing Genome Assembly and Annotation Completeness

Seppey, M., Manni, M., & Zdobnov, E. M. (2019) · Methods in molecular biology · doi:10.1007/978-1-4939-9173-0_14 · Cited by 2,242

Definitions, methods, and applications in interpretable machine learning

Murdoch, W. J., Singh, C., Kumbier, K., Abbasi-Asl, R., & Yu, B. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1900654116 · Cited by 2,167

Disentangling type 2 diabetes and metformin treatment signatures in the human gut microbiota

MetaHIT consortium, Forslund, K., Hildebrand, F., Nielsen, T., Falony, G., Le Chatelier, E., Sunagawa, S., Prifti, E., Vieira-Silva, S., Gudmundsdottir, V., et al. (2015) · Nature · doi:10.1038/nature15766 · Cited by 2,116

UMI-tools: modeling sequencing errors in Unique Molecular Identifiers to improve quantification accuracyPreprint

Smith, T. S., Heger, A., & Sudbery, I. M. (2017) · Genome Research · doi:10.1101/gr.209601.116 · Cited by 2,072

ggmap: Spatial Visualization with ggplot2

Kahle, D. J., & Wickham, H. (2013) · The R Journal · doi:10.32614/rj-2013-014 · Cited by 2,126

Human gut microbes impact host serum metabolome and insulin sensitivity

Pedersen, H. K., Gudmundsdottir, V., Nielsen, H. B., Hyotylainen, T., Nielsen, T., Jensen, B. A. H., Forslund, K., Hildebrand, F., Prifti, E., Falony, G., et al. (2016) · Nature · doi:10.1038/nature18646 · Cited by 2,116

Shared and distinct transcriptomic cell types across neocortical areas

Tasic, B., Yao, Z., Graybuck, L. T., Smith, K. A., Nguyen, T. N., Bertagnolli, D., Goldy, J., Garren, E., Economo, M. N., Viswanathan, S., et al. (2018) · Nature · doi:10.1038/s41586-018-0654-5 · Cited by 1,746

Temporal development of the gut microbiome in early childhood from the TEDDY study

Stewart, C. J., Ajami, N. J., O’Brien, J. L., Hutchinson, D. S., Smith, D. P., Wong, M. C., Ross, M. C., Lloyd, R. E., Doddapaneni, H., Metcalf, G., et al. (2018) · Nature · doi:10.1038/s41586-018-0617-x · Cited by 2,055

The neuroactive potential of the human gut microbiota in quality of life and depression

Valles-Colomer, M., Falony, G., Darzi, Y., Tigchelaar, E. F., Wang, J., Tito, R. Y., Schiweck, C., Kurilshikov, A., Joossens, M., Wijmenga, C., et al. (2019) · Nature Microbiology · doi:10.1038/s41564-018-0337-x · Cited by 1,963

Google Scholar, Web of Science, and Scopus: A systematic comparison of citations in 252 subject categories

Martín-Martín, A., Orduna-Malea, E., Thelwall, M., & Delgado López-Cózar, E. (2018) · Journal of Informetrics · doi:10.1016/j.joi.2018.09.002 · Cited by 1,990

TGFβ drives immune evasion in genetically reconstituted colon cancer metastasis

Tauriello, D. V. F., Palomo-Ponce, S., Stork, D., Berenguer-Llergo, A., Badia-Ramentol, J., Iglesias, M., Sevillano, M., Ibiza, S., Cañellas, A., Hernando-Momblona, X., et al. (2018) · Nature · doi:10.1038/nature25492 · Cited by 1,851

GOplot: an R package for visually combining expression data with functional analysis

Walter, W., Sánchez‐Cabo, F., & Ricote, M. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btv300 · Cited by 1,756

Fecal microbiota transplant promotes response in immunotherapy-refractory melanoma patients

Baruch, E. N., Youngster, I., Ben-Betzalel, G., Ortenberg, R., Lahat, A., Katz, L., Adler, K., Dick-Necula, D., Raskin, S., Bloch, N., et al. (2021) · Science · doi:10.1126/science.abb5920 · Cited by 1,757

Adult mouse cortical cell taxonomy revealed by single cell transcriptomics

Tasic, B., Menon, V., Nguyen, T. N., Kim, T. K., Jarsky, T., Yao, Z., Levi, B., Gray, L. T., Sorensen, S. A., Dolbeare, T., et al. (2016) · Nature Neuroscience · doi:10.1038/nn.4216 · Cited by 1,714

Dates and Times Made Easy with lubridate

Grolemund, G., & Wickham, H. (2011) · Journal of Statistical Software · doi:10.18637/jss.v040.i03 · Cited by 1,696

Web-based survival analysis tool tailored for medical research (KMplot): Development and implementation

Lánczky, A., & Győrffy, B. (2021) · Journal of Medical Internet Research · doi:10.2196/27633 · Cited by 1,694

The support of human genetic evidence for approved drug indications

Nelson, M. R., Tipney, H., Painter, J. L., Shen, J., Nicoletti, P., Shen, Y., Floratos, A., Sham, P. C., Li, M. J., Wang, J., et al. (2015) · Nature Genetics · doi:10.1038/ng.3314 · Cited by 1,666

The Colletotrichum gloeosporioides species complex

Weir, B. S., Johnston, P. R., & Damm, U. (2012) · Studies in Mycology · doi:10.3114/sim0011 · Cited by 1,646

iDEP: an integrated web application for differential expression and pathway analysis of RNA-Seq data

Ge, X., Son, E., & Yao, R. (2018) · BMC Bioinformatics · doi:10.1186/s12859-018-2486-6 · Cited by 1,677

Equivalence Testing for Psychological Research: A Tutorial

Lakens, D., Scheel, A. M., & Isager, P. M. (2018) · Advances in Methods and Practices in Psychological Science · doi:10.1177/2515245918770963 · Cited by 1,560

Recovery of genomes from metagenomes via a dereplication, aggregation and scoring strategy

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Visualizations with statistical details: The 'ggstatsplot' approach

Patil, I. (2021) · The Journal of Open Source Software · doi:10.21105/joss.03167 · Cited by 1,504

Severe COVID-19 Is Marked by a Dysregulated Myeloid Cell Compartment

Schulte-Schrepping, J., Reusch, N., Paclik, D., Baßler, K., Schlickeiser, S., Zhang, B., Krämer, B., Krammer, T., Brumhard, S., Bonaguro, L., et al. (2020) · Cell · doi:10.1016/j.cell.2020.08.001 · Cited by 1,461

Benchmarking atlas-level data integration in single-cell genomics

Luecken, M. D., Büttner, M., Chaichoompu, K., Danese, A., Interlandi, M., Mueller, M. F., Strobl, D. C., Zappia, L., Dugas, M., Colomé-Tatché, M., et al. (2022) · Nature Methods · doi:10.1038/s41592-021-01336-8 · Cited by 1,438

Gut-microbiota-targeted diets modulate human immune status

Wastyk, H. C., Fragiadakis, G. K., Perelman, D., Dahan, D., Merrill, B. D., Yu, F. B., Topf, M., Gonzalez, C. G., Van Treuren, W., Han, S., et al. (2021) · Cell · doi:10.1016/j.cell.2021.06.019 · Cited by 1,385

landscapemetrics : an open‐source R tool to calculate landscape metrics

Hesselbarth, M., Sciaini, M., With, K. A., Wiegand, K., & Nowosad, J. (2019) · Ecography · doi:10.1111/ecog.04617 · Cited by 1,192

Clustering trees: a visualization for evaluating clusterings at multiple resolutions

Zappia, L., & Oshlack, A. (2018) · GigaScience · doi:10.1093/gigascience/giy083 · Cited by 1,064

An environment-dependent transcriptional network specifies human microglia identity

Gosselin, D., Skola, D., Coufal, N. G., Holtman, I. R., Schlachetzki, J. C. M., Sajti, E., Jaeger, B. N., O’Connor, C., Fitzpatrick, C., Pasillas, M. P., et al. (2017) · Science · doi:10.1126/science.aal3222 · Cited by 1,220

Hierarchical generalized additive models in ecology: an introduction with mgcv

Pedersen, E. J., Miller, D. L., Simpson, G. L., & Ross, N. (2019) · PeerJ · doi:10.7717/peerj.6876 · Cited by 1,225

pdp: An R Package for Constructing Partial Dependence Plots

Brandon, M. G. (2017) · The R Journal · doi:10.32614/rj-2017-016 · Cited by 1,198

Innate Immune Landscape in Early Lung Adenocarcinoma by Paired Single-Cell Analyses

Lavin, Y., Kobayashi, S., Leader, A., Amir, E.-A. D., Elefant, N., Bigenwald, C., Remark, R., Sweeney, R., Becker, C. D., Levine, J. H., et al. (2017) · Cell · doi:10.1016/j.cell.2017.04.014 · Cited by 1,209

Transmission of SARS-CoV-2 on mink farms between humans and mink and back to humans

Munnink, B. B. O., Sikkema, R. S., Nieuwenhuijse, D. F., Molenaar, R. J., Münger, E., Molenkamp, R., van der Spek, A. N., Tolsma, P., Rietveld, A., Brouwer, M., et al. (2020) · Science · doi:10.1126/science.abe5901 · Cited by 1,116

TOX is a critical regulator of tumour-specific T cell differentiation

Scott, A. C., Dündar, F., Zumbo, P., Chandran, S. S., Klebanoff, C. A., Shakiba, M., Trivedi, P., Menocal, L., Appleby, H., Camara, S., et al. (2019) · Nature · doi:10.1038/s41586-019-1324-y · Cited by 1,106

Visualization of Regression Models Using visreg

Breheny, P. J., & Burchett, W. (2017) · The R Journal · doi:10.32614/rj-2017-046 · Cited by 1,102

Modulation of Myelopoiesis Progenitors Is an Integral Component of Trained Immunity

Mitroulis, I., Ruppova, K., Wang, B., Chen, L.-S., Grzybek, M., Grinenko, T., Eugster, A., Troullinaki, M., Palladini, A., Kourtzelis, I., et al. (2018) · Cell · doi:10.1016/j.cell.2017.11.034 · Cited by 1,100

False discovery rates: a new deal

Stephens, M. (2016) · Biostatistics · doi:10.1093/biostatistics/kxw041 · Cited by 1,132

A single-cell atlas of entorhinal cortex from individuals with Alzheimer’s disease reveals cell-type-specific gene expression regulation

Grubman, A., Chew, G., Ouyang, J. F., Sun, G., Choo, X. Y., McLean, C., Simmons, R. K., Buckberry, S., Vargas-Landin, D. B., Poppe, D., et al. (2019) · Nature Neuroscience · doi:10.1038/s41593-019-0539-4 · Cited by 956

TNMplot.com: A Web Tool for the Comparison of Gene Expression in Normal, Tumor and Metastatic Tissues

Bartha, Á., & Győrffy, B. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22052622 · Cited by 1,070

Benchmarking of participant-level confound regression strategies for the control of motion artifact in studies of functional connectivity

Ciric, R., Wolf, D. H., Power, J. D., Roalf, D. R., Baum, G. L., Ruparel, K., Shinohara, R. T., Elliott, M. A., Eickhoff, S. B., Davatzikos, C., et al. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.03.020 · Cited by 1,042

Balance between community assembly processes mediates species coexistence in agricultural soil microbiomes across eastern China

Jiao, S., Yang, Y., Xu, Y., Zhang, J., & Lu, Y. (2019) · The ISME Journal · doi:10.1038/s41396-019-0522-9 · Cited by 1,054

Interrogation of the Microenvironmental Landscape in Brain Tumors Reveals Disease-Specific Alterations of Immune Cells

Klemm, F., Maas, R. R., Bowman, R. L., Kornete, M., Soukup, K., Nassiri, S., Brouland, J., Iacobuzio–Donahue, C. A., Brennan, C., Tabar, V. S., et al. (2020) · Cell · doi:10.1016/j.cell.2020.05.007 · Cited by 1,030

A consensus guide to capturing the ability to inhibit actions and impulsive behaviors in the stop-signal task

Verbruggen, F., Aron, A. R., Band, G. P., Beste, C., Bissett, P. G., Brockett, A. T., Brown, J. W., Chamberlain, S. R., Chambers, C. D., Colonius, H., et al. (2019) · eLife · doi:10.7554/elife.46323 · Cited by 990

Visualization in Bayesian Workflow

Gabry, J., Simpson, D., Vehtari, A., Betancourt, M., & Gelman, A. (2019) · Journal of the Royal Statistical Society Series A: Statistics in Society · doi:10.1111/rssa.12378 · Cited by 1,122

Practical innovations for high-throughput amplicon sequencing

Lundberg, D. S., Yourstone, S., Mieczkowski, P. A., Jones, C. D., & Dangl, J. L. (2013) · Nature Methods · doi:10.1038/nmeth.2634 · Cited by 1,012

An Immune Atlas of Clear Cell Renal Cell Carcinoma

Chevrier, S., Levine, J., Zanotelli, V. R., Siliņa, K., Schulz, D., Bacac, M., Ries, C. H., Ailles, L., Jewett, M. A. S., Moch, H., et al. (2017) · Cell · doi:10.1016/j.cell.2017.04.016 · Cited by 1,036

A genome-wide association study with 1,126,563 individuals identifies new risk loci for Alzheimer’s disease

Wightman, D. P., Jansen, I. E., Savage, J. E., Shadrin, A. A., Bahrami, S., Holland, D., Rongve, A., Børte, S., Winsvold, B. S., Drange, O. K., et al. (2021) · Nature Genetics · doi:10.1038/s41588-021-00921-z · Cited by 1,011

Short-term and Long-term Rates of Postacute Sequelae of SARS-CoV-2 Infection

Groff, D., Sun, A., Ssentongo, A. E., Ba, D. M., Parsons, N., Poudel, G. R., Lekoubou, A., Oh, J. S., Ericson, J. E., Ssentongo, P., et al. (2021) · JAMA Network Open · doi:10.1001/jamanetworkopen.2021.28568 · Cited by 1,010

Host genotype and age shape the leaf and root microbiomes of a wild perennial plant

Wagner, M. R., Lundberg, D. S., del Rio, T. G., Tringe, S. G., Dangl, J. L., & Mitchell‐Olds, T. (2016) · Nature Communications · doi:10.1038/ncomms12151 · Cited by 1,019

The gut mycobiome of the Human Microbiome Project healthy cohort

Nash, A. K., Auchtung, T. A., Wong, M. C., Smith, D. P., Gesell, J. R., Ross, M. C., Stewart, C. J., Metcalf, G., Muzny, D. M., Gibbs, R. A., et al. (2017) · Microbiome · doi:10.1186/s40168-017-0373-4 · Cited by 1,039

Quantitative Proteomics of the Cancer Cell Line Encyclopedia

Nusinow, D. P., Szpyt, J., Ghandi, M., Rose, C. M., McDonald, E. R., Kalocsay, M., Jané-Valbuena, J., Gelfand, E., Schweppe, D. K., Jedrychowski, M., et al. (2020) · Cell · doi:10.1016/j.cell.2019.12.023 · Cited by 957

m6A mRNA methylation controls T cell homeostasis by targeting the IL-7/STAT5/SOCS pathways

Li, H., Tong, J., Zhu, S., Batista, P. J., Duffy, E. E., Zhao, J., Bailis, W., Cao, G., Kroehling, L., Chen, Y. G., et al. (2017) · Nature · doi:10.1038/nature23450 · Cited by 974

Swarm: robust and fast clustering method for amplicon-based studies

Mahé, F., Rognes, T., Quince, C., de Vargas, C., & Dunthorn, M. (2014) · PeerJ · doi:10.7717/peerj.593 · Cited by 1,049

Plot-scale evidence of tundra vegetation change and links to recent summer warming

Elmendorf, S. C., Henry, G. H. R., Hollister, R. D., Björk, R. G., Boulanger‐Lapointe, N., Cooper, E. J., Cornelissen, J. H. C., Day, T. A., Dorrepaal, E., Elumeeva, T. G., et al. (2012) · Nature Climate Change · doi:10.1038/nclimate1465 · Cited by 980

Predicting non-small cell lung cancer prognosis by fully automated microscopic pathology image features

Yu, K.-H., Zhang, C., Berry, G. J., Altman, R. B., Ré, C., Rubin, D. L., & Snyder, M. (2016) · Nature Communications · doi:10.1038/ncomms12474 · Cited by 972

Wild Mouse Gut Microbiota Promotes Host Fitness and Improves Disease Resistance

Rosshart, S. P., Vassallo, B. G., Angeletti, D., Hutchinson, D. S., Morgan, A. P., Takeda, K., Hickman, H. D., McCulloch, J. A., Badger, J. H., Ajami, N. J., et al. (2017) · Cell · doi:10.1016/j.cell.2017.09.016 · Cited by 862

Characterising long COVID: a living systematic review

Michelen, M., Cheng, V., Manoharan, L., Elkheir, N., Dagens, A., Hastie, C., O’Hara, M. E., Suett, J. C., Dahmash, D. T., Bugaeva, P., et al. (2021) · BMJ Global Health · doi:10.1136/bmjgh-2021-005427 · Cited by 1,004

Root microbiota drive direct integration of phosphate stress and immunity

Castrillo, G., Teixeira, P. J. P. L., Paredes, S. H., Law, T. F., de Lorenzo, L., Feltcher, M. E., Finkel, O. M., Breakfield, N. W., Mieczkowski, P. A., Jones, C. D., et al. (2017) · Nature · doi:10.1038/nature21417 · Cited by 962

Remdesivir: A Review of Its Discovery and Development Leading to Emergency Use Authorization for Treatment of COVID-19

Eastman, R. T., Roth, J. S., Brimacombe, K. R., Simeonov, A. M., Shen, M., Patnaik, S., & Hall, M. D. (2020) · ACS Central Science · doi:10.1021/acscentsci.0c00489 · Cited by 963

RNA-Seq Signatures Normalized by mRNA Abundance Allow Absolute Deconvolution of Human Immune Cell Types

Monaco, G., Lee, B., Xu, W., Mustafah, S., Hwang, Y. Y., Carré, C., Burdin, N., Visan, L., Ceccarelli, M., Poidinger, M., et al. (2019) · Cell Reports · doi:10.1016/j.celrep.2019.01.041 · Cited by 958

Evaluating the relationship between circulating lipoprotein lipids and apolipoproteins with risk of coronary heart disease: A multivariable Mendelian randomisation analysis

Richardson, T. G., Sanderson, E., Palmer, T. M., Ala-Korpela, M., Ference, B. A., Davey Smith, G., & Holmes, M. V. (2020) · PLOS Medicine · doi:10.1371/journal.pmed.1003062 · Cited by 843

Diagnostic Yield and Clinical Utility of Sequencing Familial Hypercholesterolemia Genes in Patients With Severe Hypercholesterolemia

Khera, A. V., Won, H.-H., Peloso, G. M., Lawson, K. S., Bartz, T. M., Deng, X., van Leeuwen, E. M., Natarajan, P., Emdin, C. A., Bick, A. G., et al. (2016) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2016.03.520 · Cited by 942

Phytochromes function as thermosensors in Arabidopsis

Jung, J., Domijan, M., Klose, C., Biswas, S., Ezer, D., Gao, M., Khattak, A. K., Box, M. S., Charoensawan, V., Cortijo, S., et al. (2016) · Science · doi:10.1126/science.aaf6005 · Cited by 964

ggseqlogo: a versatile R package for drawing sequence logos

Wagih, O. (2017) · Bioinformatics · doi:10.1093/bioinformatics/btx469 · Cited by 933

c-Jun overexpression in CAR T cells induces exhaustion resistance

Lynn, R. C., Weber, E. W., Sotillo, E., Gennert, D., Xu, P., Good, Z., Anbunathan, H., Lattin, J., Jones, R., Tieu, V., et al. (2019) · Nature · doi:10.1038/s41586-019-1805-z · Cited by 891

Google Scholar, Microsoft Academic, Scopus, Dimensions, Web of Science, and OpenCitations’ COCI: a multidisciplinary comparison of coverage via citations

Martín‐Martín, A., Thelwall, M. A., Orduña‐Malea, E., & Delgado López-Cózar, E. (2020) · LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) · Cited by 916

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The Preclinical Alzheimer Cognitive Composite: Measuring Amyloid-Related Decline

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Role of TP53 mutations in the origin and evolution of therapy-related acute myeloid leukaemia

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Combined single-cell and spatial transcriptomics reveal the molecular, cellular and spatial bone marrow niche organization

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ggfortify: Unified Interface to Visualize Statistical Results of Popular R Packages

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Lost, but Found with Nile Red: A Novel Method for Detecting and Quantifying Small Microplastics (1 mm to 20 μm) in Environmental Samples

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ggplot2

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Graphs with ggplot2

Ryan, C. (2021) · CRC Press eBooks · doi:10.1201/9781003106845-12

^DOWNLOAD E.B.O.O.K.# ggplot2: Elegant Graphics for Data Analysis (Use R!) Full PDF

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DOWNLOAD in [PDF] ggplot2: Elegant Graphics for Data Analysis (Use R!) Full Pages

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