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9 results on '"Christopher R. Keefe"'

1. Facilitating bioinformatics reproducibility with QIIME 2 Provenance Replay.

Author

Christopher R Keefe, Matthew R Dillon, Elizabeth Gehret, Chloe Herman, Mary Jewell, Colin V Wood, Evan Bolyen, and J Gregory Caporaso

Subjects
Biology (General), QH301-705.5
Abstract

Study reproducibility is essential to corroborate, build on, and learn from the results of scientific research but is notoriously challenging in bioinformatics, which often involves large data sets and complex analytic workflows involving many different tools. Additionally, many biologists are not trained in how to effectively record their bioinformatics analysis steps to ensure reproducibility, so critical information is often missing. Software tools used in bioinformatics can automate provenance tracking of the results they generate, removing most barriers to bioinformatics reproducibility. Here we present an implementation of that idea, Provenance Replay, a tool for generating new executable code from results generated with the QIIME 2 bioinformatics platform, and discuss considerations for bioinformatics developers who wish to implement similar functionality in their software.

Published
2023
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2. Experiences and lessons learned from two virtual, hands-on microbiome bioinformatics workshops.

Author

Matthew R. Dillon, Evan Bolyen, Anja Adamov, Aeriel Belk, Emily Borsom, Zachary Burcham, Justine W. Debelius, Heather Deel, Alex Emmons, Mehrbod Estaki, Chloe Herman, Christopher R. Keefe, Jamie T. Morton, Renato R. M. Oliveira, Andrew Sanchez, Anthony Simard, Yoshiki Vazquez-Baeza, Michal Ziemski, Hazuki E. Miwa, Terry A. Kerere, Carline Coote, Richard Bonneau, Rob Knight 0001, Guilherme Oliveira, Piraveen Gopalasingam, Benjamin D. Kaehler, Emily K. Cope, Jessica L. Metcalf, Michael S. Robeson II, Nicholas A. Bokulich, and J. Gregory Caporaso

Published
2021
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3. Predicting Neurodegenerative Disease Using Prepathology Gut Microbiota Composition: a Longitudinal Study in Mice Modeling Alzheimer’s Disease Pathologies

Author

Emily M. Borsom, Kathryn Conn, Christopher R. Keefe, Chloe Herman, Gabrielle M. Orsini, Allyson H. Hirsch, Melanie Palma Avila, George Testo, Sierra A. Jaramillo, Evan Bolyen, Keehoon Lee, J. Gregory Caporaso, and Emily Cope

Subjects
Microbiology (medical), Infectious Diseases, General Immunology and Microbiology, Ecology, Physiology, Genetics, Cell Biology
Abstract

The gut microbiota-brain axis is suspected to contribute to the development of Alzheimer’s Disease (AD), a neurodegenerative disease characterized by amyloid-β plaque deposition, neurofibrillary tangles, and neuroinflammation. To evaluate the role of the gut microbiota-brain axis in AD, we characterized the gut microbiota of 3xTg-AD mice modeling amyloidosis and tauopathy and wild type (WT) genetic controls. Fecal samples were collected fortnightly from 4 to 52 weeks, and the V4 region of the 16S rRNA gene was amplified and sequenced on an Illumina MiSeq. RNA was extracted from the colon and hippocampus, converted to cDNA, and used to measure immune gene expression using RT-qPCR. Diversity metrics were calculated using QIIME 2, and a Random Forest classifier was applied to predict bacterial features that are important in predicting mouse genotype. Gut microbiota were compositionally distinct early in life between 3xTg-AD mice and WT mice (PERMANOVA 8 weeks, p = 0.001, 24 weeks, p = 0.039, and 52 weeks, p = 0.058). We demonstrate that mouse genotype was correctly predicted 90–100% using fecal microbiome composition. Finally, we demonstrate that Bacteroides species relative abundance increased over time in 3xTg-AD mice. Taken together, we demonstrate that changes bacterial gut microbiota composition at pre-pathology timepoints are predictive of development of AD pathologies.

Published
2023
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4. Influence of fecal microbiota transplantation on gut microbiota composition in transgenic mice modeling amyloid‐β plaques and neurofibrillary tangles

Author

Emily M Borsom, Christopher R Keefe, Allyson H Hirsch, Kathryn A Conn, Gabrielle M Orsini, Sierra A Jaramillo, Evan K Bolyen, Matthew R Dillon, Keehoon Lee, J. Gregory Caporaso, and Emily K Cope

Subjects
Psychiatry and Mental health, Cellular and Molecular Neuroscience, Developmental Neuroscience, Epidemiology, Health Policy, Neurology (clinical), Geriatrics and Gerontology
Published
2022
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5. Predicting neurodegenerative disease using the unique gut microbiota composition of transgenic mice modeling amyloid‐β plaques and neurofibrillary tangles

Author

Emily M Borsom, Kathryn A Conn, Christopher R Keefe, Allyson H Hirsch, Gabrielle M Orsini, Sierra A Jaramillo, George Testo, Melanie Palma Avila, Evan K Bolyen, Matthew R Dillon, Keehoon Lee, J. Gregory Caporaso, and Emily K Cope

Subjects
Psychiatry and Mental health, Cellular and Molecular Neuroscience, Developmental Neuroscience, Epidemiology, Health Policy, Neurology (clinical), Geriatrics and Gerontology
Published
2022
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6. Experiences and lessons learned from two virtual, hands-on microbiome bioinformatics workshops

Author

Emily K. Cope, Mehrbod Estaki, Terry A Kerere, Guilherme Oliveira, Andrew Sanchez, Renato R. M. Oliveira, Evan Bolyen, Nicholas A. Bokulich, Justine W. Debelius, Jessica L. Metcalf, Richard Bonneau, Chloe Herman, J. Gregory Caporaso, Emily M. Borsom, Benjamin D. Kaehler, Jamie Morton, Aeriel D. Belk, Carline Coote, Alex Emmons, Anja Adamov, Matthew R. Dillon, Rob Knight, Zachary M. Burcham, Michal Ziemski, Christopher R. Keefe, Heather Deel, Piraveen Gopalasingam, Michael S. Robeson, Anthony Simard, Hazuki E. Miwa, Yoshiki Vázquez-Baeza, and Ouellette, Francis

Subjects
0301 basic medicine, Critical Care and Emergency Medicine, Social Sciences, Cloud computing, Plan (drawing), Surveys, Bioinformatics, Mathematical Sciences, Database and Informatics Methods, 0302 clinical medicine, Sociology, Medicine and Health Sciences, Biology (General), Ecology, Event (computing), Microbiota, Software Engineering, Genomics, Biological Sciences, Professions, Computational Theory and Mathematics, Medical Microbiology, Research Design, Modeling and Simulation, Lectures, Engineering and Technology, Workshops, Psychology, 2019-20 coronavirus outbreak, Computer and Information Sciences, Coronavirus disease 2019 (COVID-19), QH301-705.5, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Microbial Genomics, Research and Analysis Methods, Microbiology, Education, Feedback, Computer Software, 03 medical and health sciences, Cellular and Molecular Neuroscience, Information and Computing Sciences, Genetics, Humans, Molecular Biology, Ecology, Evolution, Behavior and Systematics, Survey Research, business.industry, Extramural, SARS-CoV-2, Biology and Life Sciences, COVID-19, Computational Biology, Emerging Infectious Diseases, 030104 developmental biology, Instructors, People and Places, Population Groupings, Microbiome, Triage, business, 030217 neurology & neurosurgery
Abstract

In October of 2020, in response to the Coronavirus Disease 2019 (COVID-19) pandemic, our team hosted our first fully online workshop teaching the QIIME 2 microbiome bioinformatics platform. We had 75 enrolled participants who joined from at least 25 different countries on 6 continents, and we had 22 instructors on 4 continents. In the 5-day workshop, participants worked hands-on with a cloud-based shared compute cluster that we deployed for this course. The event was well received, and participants provided feedback and suggestions in a postworkshop questionnaire. In January of 2021, we followed this workshop with a second fully online workshop, incorporating lessons from the first. Here, we present details on the technology and protocols that we used to run these workshops, focusing on the first workshop and then introducing changes made for the second workshop. We discuss what worked well, what didn’t work well, and what we plan to do differently in future workshops., PLoS Computational Biology, 17 (6), ISSN:1553-734X, ISSN:1553-7358

Published
2021

7. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2

Author

Fernando Vargas, Matthew R. Dillon, Stephanie B. Orchanian, Mary L. Preuss, Daniel McDonald, Christian C. Abnet, J. Gregory Caporaso, Alexey V. Melnik, Claire Duvallet, Massoud Maher, Max von Hippel, Colin J. Brislawn, Jamie Morton, Kyle C. Weber, Patrick Rosenthal, Qiyun Zhu, Lauren J. McIver, Talima Pearson, Clarisse Marotz, Madeleine Ernst, Ruth E. Ley, Jiarong Guo, Tomasz Kosciolek, Jorden Kreps, Benjamin D. Kaehler, Deanna L. Gibson, Yilong Zhang, Kestrel Gorlick, Catherine A. Lozupone, Nicholas A. Bokulich, Jessica L. Metcalf, Daniel M. Durall, Paul Keim, Daniel Petras, Elmar Pruesse, Dan Knights, Emily K. Cope, Gavin M. Douglas, Sean M. Gibbons, Hannes Holste, Austin D. Swafford, Yong-Xin Liu, Sabah Ul-Hasan, Joslynn S. Lee, Benjamin J. Callahan, Mehrbod Estaki, Zhenjiang Zech Xu, Jordan E. Bisanz, Jennifer Fouquier, Lingjing Jiang, Justin J. J. van der Hooft, Ahmad Turan Naimey, Michael S. Robeson, Harriet Alexander, Jesse R. Zaneveld, Andrés Mauricio Caraballo-Rodríguez, Gavin A. Huttley, Antonio Gonzalez, Curtis Huttenhower, Anupriya Tripathi, Pauline Trinh, Mingxun Wang, Emily Vogtmann, Susan Holmes, Yunhu Wan, Rashmi Sinha, Irina Koester, William A. Walters, Yang Bai, Kyo Bin Kang, Luke R. Thompson, Christian F. Edwardson, Ricardo Silva, Pedro J. Torres, Gabriel A. Al-Ghalith, Stefan Janssen, Kyle Bittinger, Manimozhiyan Arumugam, Jonathan Warren, Alan K. Jarmusch, Lasse Buur Rasmussen, Rob Knight, Se Jin Song, Michael Shaffer, Sydney C. Morgan, Bryan D Martin, Peter J. Turnbaugh, C. Titus Brown, Jose A. Navas-Molina, Morgan G. I. Langille, Christopher R. Keefe, Benjamin Hillmann, Eric J. Alm, Evan Bolyen, Arron Shiffer, Louis-Félix Nothias, Christian Diener, Nicola Segata, Francesco Asnicar, Charles H. D. Williamson, Samuel L. Peoples, Amy D. Willis, Pieter C. Dorrestein, Adam R. Rivers, John Chase, Scott T. Kelley, Julia M. Gauglitz, Yoshiki Vázquez-Baeza, John R. Spear, Jai Ram Rideout, Asker Daniel Brejnrod, Erikka Loftfield, Massachusetts Institute of Technology. Department of Biological Engineering, and Massachusetts Institute of Technology. Center for Microbiome Informatics and Therapeutics

Subjects
Research program, Engineering, Databases, Factual, Bioinformatics, Biomedical Engineering, Library science, Bioengineering, Research initiative, Applied Microbiology and Biotechnology, Article, 03 medical and health sciences, 0302 clinical medicine, Bioinformatica, Humans, Life Science, 030304 developmental biology, National health, 0303 health sciences, business.industry, Extramural, Microbiota, Data Science, Computational Biology, Medical research, Chinese academy of sciences, 3. Good health, Molecular Medicine, Metagenomics, business, Partial support, Engineering research, Software, 030217 neurology & neurosurgery, Biotechnology
Abstract

QIIME 2 development was primarily funded by NSF Awards 1565100 to J.G.C. and 1565057 to R.K. Partial support was also provided by the following: grants NIH U54CA143925 (J.G.C. and T.P.) and U54MD012388 (J.G.C. and T.P.); grants from the Alfred P. Sloan Foundation (J.G.C. and R.K.); ERCSTG project MetaPG (N.S.); the Strategic Priority Research Program of the Chinese Academy of Sciences QYZDB-SSW-SMC021 (Y.B.); the Australian National Health and Medical Research Council APP1085372 (G.A.H., J.G.C., Von Bing Yap and R.K.); the Natural Sciences and Engineering Research Council (NSERC) to D.L.G.; and the State of Arizona Technology and Research Initiative Fund (TRIF), administered by the Arizona Board of Regents, through Northern Arizona University. All NCI coauthors were supported by the Intramural Research Program of the National Cancer Institute. S.M.G. and C. Diener were supported by the Washington Research Foundation Distinguished Investigator Award.

Published
2019

8. QIIME 2: Reproducible, interactive, scalable, and extensible microbiome data science

Author

Daniel Petras, Mehrbod Estaki, Kyle C. Weber, Yilong Zhang, Emily Vogtmann, Kestrel Gorlick, Eric J. Alm, Benjamin J. Callahan, Evan Bolyen, Alexey V. Melnik, Yang Bai, Gabriel A. Al-Ghalith, Louis-Félix Nothias, Elmar Pruesse, Massoud Maher, Zhenjiang Zech Xu, Gavin M. Douglas, Dan Knights, Stefan Janssen, Christopher R. Keefe, Jonathan Warren, Yong-Xin Liu, Chase Hd Williamson, Manimozhiyan Arumugam, Ii Michael S Robeson, Justin J. J. van der Hooft, Kyle Bittinger, Alan K. Jarmusch, Antonio Gonzalez, Sydney C. Morgan, Paul Keim, Stephanie B. Orchanian, Jessica L. Metcalf, Bryan D Martin, Jordan E. Bisanz, Andrés Mauricio Caraballo-Rodríguez, Curtis Huttenhower, Peter J. Turnbaugh, Arron Shiffer, Nicola Segata, Samuel L. Peoples, Hannes Holste, Ruth E. Ley, Rashmi Sinha, Ahmad Turan Naimey, Talima Pearson, Jose A. Navas-Molina, Francesco Asnicar, Michael Shaffer, Daniel McDonald, Gavin A. Huttley, Kyo Bin Kang, Jorden Kreps, Luke R. Thompson, Daniel M. Durall, Benjamin D. Kaehler, Anupriya Tripathi, Max von Hippel, Catherine A. Lozupone, Joslynn S. Lee, John Chase, Nicholas A. Bokulich, Colin J. Brislawn, Pauline Trinh, C. Titus Brown, Harriet Alexander, Matthew R. Dillon, Clarisse Marotz, Ricardo Silva, Jamie Morton, Morgan G. I. Langille, Mary L. Preuss, Deanna L. Gibson, Pieter C. Dorrestein, J. Gregory Caporaso, Pedro J. Torres, Yunhu Wan, Christian F. Edwardson, William A. Walters, Claire Duvallet, Benjamin Hillmann, Erikka Loftfield, Mingxun Wang, Fernando Vargas, Patrick Rosenthal, Susan Holmes, Se Jin Song, Madeleine Ernst, Irina Koester, Sabah Ul-Hasan, Lasse Buur Rasmussen, Rob Knight, Christian C. Abnet, Lauren J. McIver, Austin D. Swafford, Emily K. Cope, Lingjing Jiang, Jiarong Guo, Tomasz Kosciolek, Scott T. Kelley, Julia M. Gauglitz, Yoshiki Vázquez-Baeza, Amy D. Willis, Adam R. Rivers, Jennifer Fouquier, Jesse R. Zaneveld, John R. Spear, Jai Ram Rideout, and Asker Daniel Brejnrod

Subjects
Automated data, Computer science, Scalability, Microbiome, Data science, Shotgun metagenomics, Visualization
Abstract

We present QIIME 2, an open-source microbiome data science platform accessible to users spanning the microbiome research ecosystem, from scientists and engineers to clinicians and policy makers. QIIME 2 provides new features that will drive the next generation of microbiome research. These include interactive spatial and temporal analysis and visualization tools, support for metabolomics and shotgun metagenomics analysis, and automated data provenance tracking to ensure reproducible, transparent microbiome data science.

Published
2018
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9. Author Correction: Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2

Author

Jamie Morton, Ruth E. Ley, Samuel L. Peoples, Dan Knights, Yong-Xin Liu, Gavin M. Douglas, Colin J. Brislawn, Fernando Vargas, Yunhu Wan, Daniel McDonald, Sean M. Gibbons, Daniel Petras, Amy D. Willis, Stephanie B. Orchanian, Rashmi Sinha, J. Gregory Caporaso, Gabriel A. Al-Ghalith, Claire Duvallet, Adam R. Rivers, Kyo Bin Kang, Lasse Buur Rasmussen, Pieter C. Dorrestein, Benjamin J. Callahan, Michael Shaffer, Rob Knight, Patrick Rosenthal, Madeleine Ernst, Matthew R. Dillon, Christian F. Edwardson, Qiyun Zhu, Yang Bai, Alexey V. Melnik, Daniel M. Durall, Christian C. Abnet, Lauren J. McIver, Julia M. Gauglitz, Jiarong Guo, Joslynn S. Lee, Charles H. D. Williamson, Tomasz Kosciolek, Massoud Maher, Emily Vogtmann, Mary L. Preuss, Kyle Bittinger, Alan K. Jarmusch, Mingxun Wang, Jose A. Navas-Molina, Susan Holmes, Michael S. Robeson, Manimozhiyan Arumugam, C. Titus Brown, Zhenjiang Zech Xu, Harriet Alexander, Nicola Segata, John Chase, Francesco Asnicar, Se Jin Song, Yoshiki Vázquez-Baeza, Sydney C. Morgan, Austin D. Swafford, Justin J. J. van der Hooft, Irina Koester, Stefan Janssen, Ahmad Turan Naimey, Antonio Gonzalez, Jessica L. Metcalf, Gavin A. Huttley, Elmar Pruesse, Scott T. Kelley, Jonathan Warren, Talima Pearson, Anupriya Tripathi, Luke R. Thompson, Sabah Ul-Hasan, Peter J. Turnbaugh, Emily K. Cope, Christopher R. Keefe, Hannes Holste, Catherine A. Lozupone, Ricardo Silva, Pedro J. Torres, Max von Hippel, Eric J. Alm, Evan Bolyen, Jordan E. Bisanz, Lingjing Jiang, Louis-Félix Nothias, Andrés Mauricio Caraballo-Rodríguez, William A. Walters, Curtis Huttenhower, Clarisse Marotz, Kyle C. Weber, Yilong Zhang, Kestrel Gorlick, Paul Keim, Asker Daniel Brejnrod, Deanna L. Gibson, Morgan G. I. Langille, Jennifer Fouquier, Jesse R. Zaneveld, Benjamin Hillmann, Mehrbod Estaki, John R. Spear, Jai Ram Rideout, Jorden Kreps, Benjamin D. Kaehler, Pauline Trinh, Nicholas A. Bokulich, Erikka Loftfield, Bryan D Martin, Arron Shiffer, and Christian Diener

Subjects
0303 health sciences, Information retrieval, Bioinformatics, Computer science, Published Erratum, Biomedical Engineering, mothur, Bioengineering, Applied Microbiology and Biotechnology, Bioconductor, 03 medical and health sciences, 0302 clinical medicine, Bioinformatica, Life Science, Molecular Medicine, 030217 neurology & neurosurgery, 030304 developmental biology, Biotechnology
Abstract

In the version of this article initially published, some reference citations were incorrect. The three references to Jupyter Notebooks should have cited Kluyver et al. instead of Gonzalez et al. The reference to Qiita should have cited Gonzalez et al. instead of Schloss et al. The reference to mothur should have cited Schloss et al. instead of McMurdie & Holmes. The reference to phyloseq should have cited McMurdie & Holmes instead of Huber et al. The reference to Bioconductor should have cited Huber et al. instead of Franzosa et al. And the reference to the biobakery suite should have cited Franzosa et al. instead of Kluyver et al. The errors have been corrected in the HTML and PDF versions of the article.

Published
2019
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