ggplot2: Elegant Graphics for Data Analysis

A protocol for conducting and presenting results of regression‐type analyses

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Global Matrix 3.0 Physical Activity Report Card Grades for Children and Youth: Results and Analysis From 49 Countries

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Examination of real-time fluctuations in suicidal ideation and its risk factors: Results from two ecological momentary assessment studies

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In vitro generation of human pluripotent stem cell derived lung organoids

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variancePartition: interpreting drivers of variation in complex gene expression studies

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Medical students' attitude towards artificial intelligence: a multicentre survey

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Soil enzyme activities, microbial communities, and carbon and nitrogen availability in organic agroecosystems across an intensively-managed agricultural landscape

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Human iPSC-based modeling of late-onset disease via progerin-induced aging

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A phase Ib trial of personalized neoantigen therapy plus anti-PD-1 in patients with advanced melanoma, non-small cell lung cancer, or bladder cancer

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tmap : Thematic Maps in R

Tennekes, M. (2018) · Journal of Statistical Software · doi:10.18637/jss.v084.i06 · Cited by 765

Innate Immune Activity Conditions the Effect of Regulatory Variants upon Monocyte Gene Expression

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Spontaneous epigenetic variation in the Arabidopsis thaliana methylome

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TREM2 regulates microglial cholesterol metabolism upon chronic phagocytic challenge

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Opposite Roles of Salicylic Acid Receptors NPR1 and NPR3/NPR4 in Transcriptional Regulation of Plant Immunity

Ding, Y., Sun, T., Ao, K., Peng, Y., Zhang, Y., Li, X., & Zhang, Y. (2018) · Cell · doi:10.1016/j.cell.2018.03.044 · Cited by 735

A specialized metabolic network selectively modulates Arabidopsis root microbiota

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The early spread and epidemic ignition of HIV-1 in human populations

Faria, N. R., Rambaut, A., Suchard, M. A., Baele, G., Bedford, T., Ward, M. J., Tatem, A. J., de Sousa, J. D., Arinaminpathy, N., Pépin, J., et al. (2014) · Science · doi:10.1126/science.1256739 · Cited by 830

Estimating infectiousness throughout SARS-CoV-2 infection course

Jones, T. C., Biele, G., Mühlemann, B., Veith, T., Schneider, J. A., Beheim-Schwarzbach, J., Bleicker, T., Tesch, J., Schmidt, M. L., Sander, L. E., et al. (2021) · Science · doi:10.1126/science.abi5273 · Cited by 752

Conditionally Rare Taxa Disproportionately Contribute to Temporal Changes in Microbial Diversity

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ampvis2: an R package to analyse and visualise 16S rRNA amplicon dataPreprint

Andersen, K. S., Kirkegaard, R. H., Karst, S. M., & Albertsen, M. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/299537 · Cited by 741

Quantifying Mental Health Signals in Twitter

Coppersmith, G., Dredze, M., & Harman, C. (2014) · Proceedings of the Workshop on Computational Linguistics and Clinical Psychology: From Linguistic Signal to Clinical Reality · doi:10.3115/v1/w14-3207 · Cited by 722

Quantifying the impact of physical distance measures on the transmission of COVID-19 in the UK

CMMID COVID-19 working group, Jarvis, C. I., Van Zandvoort, K., Gimma, A., Prem, K., Klepac, P., Rubin, G. J., & Edmunds, W. J. (2020) · BMC Medicine · doi:10.1186/s12916-020-01597-8 · Cited by 720

Wordbank: an open repository for developmental vocabulary data

Frank, M. C., Braginsky, M., Yurovsky, D., & Marchman, V. A. (2016) · Journal of Child Language · doi:10.1017/s0305000916000209 · Cited by 717

ClipKIT: A multiple sequence alignment trimming software for accurate phylogenomic inference

Steenwyk, J. L., Buida, T. J., Li, Y., Shen, X., & Rokas, A. (2020) · PLoS Biology · doi:10.1371/journal.pbio.3001007 · Cited by 711

Factors Associated with COVID-19 Vaccine Hesitancy

Soares, P., Rocha, J. V., Moniz, M., Gama, A. F., Laires, P. A., Pedro, A. R., Dias, S., Leite, A., & Nunes, C. (2021) · Vaccines · doi:10.3390/vaccines9030300 · Cited by 700

De novo assembly, annotation, and comparative analysis of 26 diverse maize genomes

Hufford, M. B., Seetharam, A. S., Woodhouse, M. R., Chougule, K. M., Ou, S., Liu, J., Ricci, W. A., Guo, T., Olson, A., Qiu, Y., et al. (2021) · Science · doi:10.1126/science.abg5289 · Cited by 747

Therapy-Induced Evolution of Human Lung Cancer Revealed by Single-Cell RNA Sequencing

Maynard, A., McCoach, C. E., Rotow, J. K., Harris, L., Haderk, F., Kerr, D. L., Yu, E. A., Schenk, E. L., Tan, W., Zee, A., et al. (2020) · Cell · doi:10.1016/j.cell.2020.07.017 · Cited by 719

Maternal gut and breast milk microbiota affect infant gut antibiotic resistome and mobile genetic elements

Pärnänen, K. M. M., Karkman, A., Hultman, J., Lyra, C., Bengtsson‐Palme, J., Larsson, D. G. J., Rautava, S., Isolauri, E., Salminen, S., Kumar, H., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-06393-w · Cited by 690

Establishment and cryptic transmission of Zika virus in Brazil and the Americas

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Proliferating Transitory T Cells with an Effector-like Transcriptional Signature Emerge from PD-1+ Stem-like CD8+ T Cells during Chronic Infection

Hudson, W. H., Gensheimer, J., Hashimoto, M., Wieland, A., Valanparambil, R. M., Li, P., Lin, J.-X., Konieczny, B. T., Im, S. J., Freeman, G. J., et al. (2019) · Immunity · doi:10.1016/j.immuni.2019.11.002 · Cited by 656

A colorimetric RT-LAMP assay and LAMP-sequencing for detecting SARS-CoV-2 RNA in clinical samples

Thi, V. L. D., Herbst, K., Börner, K., Meurer, M., Kremer, L. P. M., Kirrmaier, D., Freistaedter, A., Papagiannidis, D., Galmozzi, C. V., Stanifer, M. L., et al. (2020) · Science Translational Medicine · doi:10.1126/scitranslmed.abc7075 · Cited by 673

The tumor microenvironment underlies acquired resistance to CSF-1R inhibition in gliomas

Quail, D. F., Bowman, R. L., Akkari, L., Quick, M. L., Schuhmacher, A. J., Huse, J. T., Holland, E. C., Sutton, J. C., & Joyce, J. A. (2016) · Science · doi:10.1126/science.aad3018 · Cited by 684

Relationships between phyllosphere bacterial communities and plant functional traits in a neotropical forest

Kembel, S. W., O’Connor, T. K., Arnold, H. K., Hubbell, S. P., Wright, S. J., & Green, J. L. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1216057111 · Cited by 674

Atlas of Subcellular RNA Localization Revealed by APEX-Seq

Fazal, F. M., Han, S., Parker, K. R., Kaewsapsak, P., Xu, J., Boettiger, A. N., Chang, H. Y., & Ting, A. Y. (2019) · Cell · doi:10.1016/j.cell.2019.05.027 · Cited by 677

heatmaply: an R package for creating interactive cluster heatmaps for online publishing

Galili, T., O’Callaghan, A., Sidi, J., & Sievert, C. (2017) · Bioinformatics · doi:10.1093/bioinformatics/btx657 · Cited by 662

MutationalPatterns: comprehensive genome-wide analysis of mutational processes

Blokzijl, F., Janssen, R., van Boxtel, R., & Cuppen, E. (2018) · Genome Medicine · doi:10.1186/s13073-018-0539-0 · Cited by 660

cooccur : Probabilistic Species Co-Occurrence Analysis in R

Griffith, D. M., Veech, J. A., & Marsh, C. J. (2016) · Journal of Statistical Software · doi:10.18637/jss.v069.c02 · Cited by 657

TREM2 Modulation Remodels the Tumor Myeloid Landscape Enhancing Anti-PD-1 Immunotherapy

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Extensive introgression in a malaria vector species complex revealed by phylogenomics

Fontaine, M. C., Pease, J. B., Steele, A., Waterhouse, R. M., Neafsey, D. E., Sharakhov, I. V., Jiang, X., Hall, A. B., Catteruccia, F., Kakani, E. G., et al. (2014) · Science · doi:10.1126/science.1258524 · Cited by 645

How to capitalize on a priori contrasts in linear (mixed) models: A tutorial

Schad, D. J., Vasishth, S., Hohenstein, S., & Kliegl, R. M. (2019) · Journal of Memory and Language · doi:10.1016/j.jml.2019.104038 · Cited by 74

Mapping high resolution National Soil Information Grids of China

Liu, F., Wu, H., Zhao, Y.-G., Li, C., Yang, J., Song, X., Shi, Z., Zhu, A., & Zhang, G. (2021) · 中国科学通报：英文版 · doi:10.1016/j.scib.2021.10.013 · Cited by 663

Small RNAs are modified with N-glycans and displayed on the surface of living cells

Flynn, R. A., Pedram, K., Malaker, S. A., Batista, P. J., Smith, B. A. H., Johnson, A. G., George, B. M., Majzoub, K., Villalta, P. W., Carette, J. E., et al. (2021) · Cell · doi:10.1016/j.cell.2021.04.023 · Cited by 648

Predicting consumer behavior with web search

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Bacterial community dynamics are linked to patterns of coral heat tolerance

Ziegler, M., Seneca, F., Yum, L. K., Palumbi, S. R., & Voolstra, C. R. (2017) · Nature Communications · doi:10.1038/ncomms14213 · Cited by 626

Fecal pollution can explain antibiotic resistance gene abundances in anthropogenically impacted environments

Karkman, A., Pärnänen, K., & Larsson, D. G. J. (2019) · Nature Communications · doi:10.1038/s41467-018-07992-3 · Cited by 628

High-Resolution Mapping Reveals a Conserved, Widespread, Dynamic mRNA Methylation Program in Yeast Meiosis

Schwartz, S., Agarwala, S. D., Mumbach, M. R., Jovanović, M., Mertins, P., Shishkin, A., Tabach, Y., Mikkelsen, T. S., Satija, R., Ruvkun, G., et al. (2013) · Cell · doi:10.1016/j.cell.2013.10.047 · Cited by 627

Worldwide occurrence records suggest a global decline in bee species richness

Zattara, E. E., & Aizen, M. A. (2021) · One Earth · doi:10.1016/j.oneear.2020.12.005 · Cited by 705

Data reuse and the open data citation advantage

Piwowar, H., & Vision, T. (2013) · PeerJ · doi:10.7717/peerj.175 · Cited by 629

Advancing Our Understanding of the Human Microbiome Using QIIME

Navas-Molina, J. A., Peralta‐Sánchez, J. M., González, A., McMurdie, P. J., Vázquez‐Baeza, Y., Xu, Z. Z., Ursell, L. K., Lauber, C. L., Zhou, H., Song, S. J., et al. (2013) · Methods in enzymology on CD-ROM/Methods in enzymology · doi:10.1016/b978-0-12-407863-5.00019-8 · Cited by 621

Single-nucleus and single-cell transcriptomes compared in matched cortical cell types

Bakken, T. E., Hodge, R. D., Miller, J. A., Yao, Z., Nguyen, T. N., Aevermann, B., Barkan, E., Bertagnolli, D., Casper, T., Dee, N., et al. (2018) · PLoS ONE · doi:10.1371/journal.pone.0209648 · Cited by 608

Exploiting rRNA operon copy number to investigate bacterial reproductive strategies

Roller, B. R. K., Stoddard, S. F., & Schmidt, T. M. (2016) · Nature Microbiology · doi:10.1038/nmicrobiol.2016.160 · Cited by 594

Microbial diversity drives carbon use efficiency in a model soil

Domeignoz‐Horta, L. A., Pold, G., Liu, X. A., Frey, S. D., Melillo, J. M., & DeAngelis, K. M. (2020) · Nature Communications · doi:10.1038/s41467-020-17502-z · Cited by 604

Accurate occupancy detection of an office room from light, temperature, humidity and CO 2 measurements using statistical learning models

Candanedo, L. M., & Feldheim, V. (2015) · Energy and Buildings · doi:10.1016/j.enbuild.2015.11.071 · Cited by 591

SCENITH: A Flow Cytometry-Based Method to Functionally Profile Energy Metabolism with Single-Cell Resolution

Argüello, R. J., Combes, A. J., Char, R., Gigan, J. P., Baaziz, A. I., Bousiquot, E., Camosseto, V., Samad, B., Tsui, J. L., Yan, P., et al. (2020) · Cell Metabolism · doi:10.1016/j.cmet.2020.11.007 · Cited by 607

Sexual-dimorphism in human immune system aging

Márquez, E. J., Chung, C.-H., Marches, R., Rossi, R. J., Nehar-Belaid, D., Eroglu, A., Mellert, D. J., Kuchel, G. A., Banchereau, J., & Ucar, D. (2020) · Nature Communications · doi:10.1038/s41467-020-14396-9 · Cited by 584

Rare microbial taxa as the major drivers of ecosystem multifunctionality in long-term fertilized soils

Chen, Q., Ding, J., Zhu, D., Hu, H., Delgado‐Baquerizo, M., Ma, Y., He, J., & Zhu, Y. (2019) · Soil Biology and Biochemistry · doi:10.1016/j.soilbio.2019.107686 · Cited by 578

Global biogeography of microbial nitrogen-cycling traits in soil

Albright, M., Martiny, A. C., & Martiny, J. B. H. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1601070113 · Cited by 577

Genetic drug target validation using Mendelian randomisation

Schmidt, A. F., Finan, C., Gordillo‐Marañón, M., Asselbergs, F. W., Freitag, D. F., Patel, R. S., Tyl, B., Chopade, S., Faraway, R., Zwierzyna, M., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-16969-0 · Cited by 590

Microplastic Spectral Classification Needs an Open Source Community: Open Specy to the Rescue!

Cowger, W., Steinmetz, Z., Gray, A. B., Munno, K., Lynch, J. M., Hapich, H., Primpke, S., Frond, H. D., Rochman, C. M., & Herodotou, O. (2021) · Analytical Chemistry · doi:10.1021/acs.analchem.1c00123 · Cited by 609

One fungus, which genes? Development and assessment of universal primers for potential secondary fungal DNA barcodes

Stielow, J. B., Lévesque, C. A., Seifert, K. A., Meyer, W., Irinyi, L., Smits, D., Renfurm, R., Verkley, G. J. M., Groenewald, M., Chaduli, D., et al. (2015) · Persoonia - Molecular Phylogeny and Evolution of Fungi · doi:10.3767/003158515x689135 · Cited by 568

Lipidomics Profiling and Risk of Cardiovascular Disease in the Prospective Population-Based Bruneck Study

Stegemann, C., Pechlaner, R., Willeit, P., Langley, S. R., Mangino, M., Mayr, U., Menni, C., Moayyeri, A., Santer, P., Rungger, G., et al. (2014) · Circulation · doi:10.1161/circulationaha.113.002500 · Cited by 570

Single sample scoring of molecular phenotypes

Foroutan, M., Bhuva, D. D., Horan, K., Lyu, R., Cursons, J., & Davis, M. J. (2018) · BMC Bioinformatics · doi:10.1186/s12859-018-2435-4 · Cited by 561

When worry about climate change leads to climate action: How values, worry and personal responsibility relate to various climate actions

Bouman, T., Verschoor, M., Albers, C. J., Böhm, G., Fisher, S. D., Poortinga, W., Whitmarsh, L. E., & Steg, L. (2020) · Global Environmental Change · doi:10.1016/j.gloenvcha.2020.102061 · Cited by 560

Transcriptional Reprogramming of Distinct Peripheral Sensory Neuron Subtypes after Axonal Injury

Renthal, W. R., Tochitsky, I., Yang, L., Cheng, Y., Li, E., Kawaguchi, R., Geschwind, D. H., & Woolf, C. J. (2020) · Neuron · doi:10.1016/j.neuron.2020.07.026 · Cited by 559

Data driven prediction models of energy use of appliances in a low-energy house

Candanedo, L. M., Feldheim, V., & Deramaix, D. (2017) · Energy and Buildings · doi:10.1016/j.enbuild.2017.01.083 · Cited by 559

A global synthesis of animal phenological responses to climate change

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Comparison of the accuracy of human readers versus machine-learning algorithms for pigmented skin lesion classification: an open, web-based, international, diagnostic study

Tschandl, P., Codella, N., Akay, B. N., Argenziano, G., Braun, R. P., Cabo, H., Gutman, D., Halpern, A., Helba, B., Hofmann-Wellenhof, R., et al. (2019) · The Lancet Oncology · doi:10.1016/s1470-2045(19)30333-x · Cited by 555

m6A RNA Methylation Is Regulated by MicroRNAs and Promotes Reprogramming to Pluripotency

Chen, T., Hao, Y., Zhang, Y., Li, M., Wang, M., Han, W., Yong-sheng, W., Lv, Y., Hao, J., Wang, L., et al. (2015) · Cell stem cell · doi:10.1016/j.stem.2015.01.016 · Cited by 552

Widespread and Functional RNA Circularization in Localized Prostate Cancer

Chen, S., Huang, V., Xu, X., Livingstone, J., Soares, F., Jeon, J., Zeng, Y., Hua, J. T., Petricca, J., Guo, H., et al. (2019) · Cell · doi:10.1016/j.cell.2019.01.025 · Cited by 544

Routes of Acquisition of the Gut Microbiota of the Honey Bee Apis mellifera

Powell, J. E., Martinson, V. G., Urban‐Mead, K. R., & Moran, N. A. (2014) · Applied and Environmental Microbiology · doi:10.1128/aem.01861-14 · Cited by 557

The truth about metagenomics: quantifying and counteracting bias in 16S rRNA studies

Vaginal Microbiome Consortium (additional members), Brooks, J. P., Edwards, D. J., Harwich, M. D., Rivera, M. C., Fettweis, J. M., Serrano, M. G., Reris, R. A., Sheth, N. U., Huang, B., et al. (2015) · BMC Microbiology · doi:10.1186/s12866-015-0351-6 · Cited by 528

Simpson's paradox in psychological science: a practical guide

Kievit, R. A., Frankenhuis, W. E., Waldorp, L. J., & Borsboom, D. (2013) · Frontiers in Psychology · doi:10.3389/fpsyg.2013.00513 · Cited by 542

Length-independent telomere damage drives post-mitotic cardiomyocyte senescence

Anderson, R., Lagnado, A., Maggiorani, D., Walaszczyk, A., Dookun, E., Chapman, J., Birch, J., Salmonowicz, H., Ogrodnik, M., Jurk, D., et al. (2019) · The EMBO Journal · doi:10.15252/embj.2018100492 · Cited by 532

muscat detects subpopulation-specific state transitions from multi-sample multi-condition single-cell transcriptomics data

Crowell, H. L., Soneson, C., Germain, P.-L., Calini, D., Collin, L., Raposo, C., Malhotra, D., & Robinson, M. D. (2020) · Nature Communications · doi:10.1038/s41467-020-19894-4 · Cited by 515

Investigating the performance of exploratory graph analysis and traditional techniques to identify the number of latent factors: A simulation and tutorial.

Golino, H. F., Shi, D., Christensen, A. P., Garrido, L. E., Nieto, M. D., Sadana, R., Thiyagarajan, J. A., & Martínez‐Molina, A. (2020) · Psychological Methods · doi:10.1037/met0000255 · Cited by 550

Differences in vaginal microbiome in African American women versus women of European ancestry

Fettweis, J. M., Brooks, J. P., Serrano, M. G., Sheth, N. U., Girerd, P. H., Edwards, D., Strauss, J. F., Jefferson, K. K., & Buck, G. A. (2014) · Microbiology · doi:10.1099/mic.0.081034-0 · Cited by 546

Human domination of the global water cycle absent from depictions and perceptions

Abbott, B. W., Bishop, K., Zarnetske, J. P., Minaudo, C., Chapin, F. S., Krause, S., Hannah, D. M., Conner, L. G., Ellison, D., Godsey, S. E., et al. (2019) · Nature Geoscience · doi:10.1038/s41561-019-0374-y · Cited by 612

Adaptive Chromatin Remodeling Drives Glioblastoma Stem Cell Plasticity and Drug Tolerance

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Architectural design influences the diversity and structure of the built environment microbiome

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Gut vascular barrier impairment leads to intestinal bacteria dissemination and colorectal cancer metastasis to liver

Bertocchi, A., Carloni, S., Ravenda, P. S., Bertalot, G., Spadoni, I., Lo Cascio, A., Gandini, S., Lizier, M., Braga, D., Asnicar, F., et al. (2021) · Cancer Cell · doi:10.1016/j.ccell.2021.03.004 · Cited by 515

Back to Basics – The Influence of DNA Extraction and Primer Choice on Phylogenetic Analysis of Activated Sludge Communities

Albertsen, M., Karst, S. M., Ziegler, A., Kirkegaard, R. H., & Nielsen, P. H. (2015) · PLoS ONE · doi:10.1371/journal.pone.0132783 · Cited by 540

Performance Characteristics of the Abbott Architect SARS-CoV-2 IgG Assay and Seroprevalence in Boise, Idaho

Bryan, A. B., Pepper, G., Wener, M. H., Fink, S. L., Morishima, C., Chaudhary, A., Jerome, K. R., Mathias, P. C., & Greninger, A. L. (2020) · Journal of Clinical Microbiology · doi:10.1128/jcm.00941-20 · Cited by 520

Incubation period of COVID-19: a rapid systematic review and meta-analysis of observational research

McAloon, C. G., Collins, Á. B., Hunt, K., Barber, A. M., Byrne, A. W., Butler, F., Casey-Bryars, M., Griffin, J., Lane, E. A., McEvoy, D., et al. (2020) · BMJ Open · doi:10.1136/bmjopen-2020-039652 · Cited by 519

Drought Stress Results in a Compartment-Specific Restructuring of the Rice Root-Associated Microbiomes

Santos‐Medellín, C., Edwards, J. A., Liechty, Z., Nguyen, B., & Sundaresan, V. (2017) · mBio · doi:10.1128/mbio.00764-17 · Cited by 549

Genetics of gene expression in primary immune cells identifies cell type-specific master regulators and roles of HLA alleles

Fairfax, B. P., Makino, S., Radhakrishnan, J., Plant, K., Leslie, S., Dilthey, A., Ellis, P., Langford, C., Vannberg, F. O., & Knight, J. C. (2012) · Nature Genetics · doi:10.1038/ng.2205 · Cited by 486

Comparative Analyses of Vertebrate Gut Microbiomes Reveal Convergence between Birds and Bats

Song, S. J., Sanders, J. G., Delsuc, F., Metcalf, J. L., Amato, K. R., Taylor, M. W., Mazel, F., Lutz, H. L., Winker, K., Graves, G. R., et al. (2020) · mBio · doi:10.1128/mbio.02901-19 · Cited by 523

High-throughput gene targeting and phenotyping in zebrafish using CRISPR/Cas9Preprint

Varshney, G. K., Pei, W., LaFave, M. C., Idol, J., Xu, L., Gallardo, V. E., Carrington, B., Bishop, K. S., Jones, M. S., Li, M., et al. (2015) · Genome Research · doi:10.1101/gr.186379.114 · Cited by 526

Climate Change and Mental Health: A Scoping Review

Charlson, F., Ali, S., Benmarhnia, T., Pearl, M., Massazza, A., Augustinavicius, J., & Scott, J. G. (2021) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph18094486 · Cited by 507

Voyager: Exploratory Analysis via Faceted Browsing of Visualization Recommendations

Wongsuphasawat, K., Moritz, D., Anand, A., Mackinlay, J. D., Howe, B., & Heer, J. (2015) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2015.2467191 · Cited by 504

Skeletal muscle cutoff values for sarcopenia diagnosis using T10 to L5 measurements in a healthy US population

Derstine, B. A., Holcombe, S. A., Ross, B. E., Wang, N. C., Su, G. L., & Wang, S. C. (2018) · Scientific Reports · doi:10.1038/s41598-018-29825-5 · Cited by 507

SimpleITK Image-Analysis Notebooks: a Collaborative Environment for Education and Reproducible Research

Yaniv, Z., Lowekamp, B., Johnson, H. J., & Beare, R. J. (2017) · Journal of Imaging Informatics in Medicine · doi:10.1007/s10278-017-0037-8 · Cited by 537

The genetics of Mexico recapitulates Native American substructure and affects biomedical traits

Moreno-Estrada, A., Gignoux, C. R., Fernández-López, J. C., Zakharia, F., Sikora, M., Contreras, A. V., Acuña-Alonzo, V., Sandoval, K., Eng, C., Romero-Hidalgo, S., et al. (2014) · Science · doi:10.1126/science.1251688 · Cited by 478

A Quantitative Proteome Map of the Human Body

Jiang, L., Wang, M., Lin, S., Jian, R., Li, X., Chan, J., Dong, G., Fang, H., Robinson, A. E., Aguet, F., et al. (2020) · Cell · doi:10.1016/j.cell.2020.08.036 · Cited by 458

Large-scale genome sequencing of mycorrhizal fungi provides insights into the early evolution of symbiotic traits

Miyauchi, S., Kiss, E., Kuo, A., Drula, É., Kohler, A., Sánchez‐García, M., Morin, E., Andreopoulos, B., Barry, K., Bonito, G. M., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-18795-w · Cited by 518

Global patterns of phosphatase activity in natural soils

Margalef, O., Sardans, J., Fernández‐Martínez, M., Molowny‐Horas, R., Janssens, I. A., Ciais, P., Goll, D. S., Richter, A. A., Obersteiner, M. H., Asensio, D., et al. (2017) · Scientific Reports · doi:10.1038/s41598-017-01418-8 · Cited by 499

Task-induced brain state manipulation improves prediction of individual traits

Greene, A. S., Gao, S., Scheinost, D., & Constable, R. T. (2018) · Nature Communications · doi:10.1038/s41467-018-04920-3 · Cited by 498

Transcriptional Architecture of Synaptic Communication Delineates GABAergic Neuron Identity

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Increasing Prevalence of Myopia in Europe and the Impact of Education

Williams, K. M., Bertelsen, G., Cumberland, P. M., Wolfram, C., Verhoeven, V. J. M., Anastasopoulos, E., Buitendijk, G. H. S., Cougnard‐Grégoire, A., Creuzot-Garcher, C. P., Erke, M. G., et al. (2015) · Ophthalmology · doi:10.1016/j.ophtha.2015.03.018 · Cited by 497

Molecular Pathways of Colon Inflammation Induced by Cancer Immunotherapy

Luoma, A. M., Suo, S., Williams, H. L., Sharova, T., Sullivan, K., Manos, M., Bowling, P., Hodi, F. S., Rahma, O., Sullivan, R. J., et al. (2020) · Cell · doi:10.1016/j.cell.2020.06.001 · Cited by 484

The heterogeneity of human CD127+ innate lymphoid cells revealed by single-cell RNA sequencing

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ggtern : Ternary Diagrams Using ggplot2

Hamilton, N. E., & Ferry, M. (2018) · Journal of Statistical Software · doi:10.18637/jss.v087.c03 · Cited by 491

ggplot2

Wickham, H. (2016) · Use R! · doi:10.1007/978-3-319-24277-4 · Cited by 34,873

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

PDF, ^. E. B. O. O. K. #. G. E. G. F. D. A. (. R. F. (2020) · Zenodo (CERN European Organization for Nuclear Research) · doi:10.5281/zenodo.4189363

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

Pages, D. I. [. G. E. G. F. D. A. (. R. F. (2020) · Zenodo (CERN European Organization for Nuclear Research) · doi:10.5281/zenodo.4188991

Visualization with ggplot2

Paul, A. (2025) · Chapman & Hall/CRC eBooks · doi:10.1201/9781003423386-8