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4. Quantitative Metaproteomics in Microbiomes of Diverse Complexity via Data-dependent and Data-independent Acquisition Mass Spectrometry

Author

Mehta, Subina P and Pratik Jagtap

Abstract

While many taxonomic members of microbiomes are mostly known, there are still some undetected taxa.Functional unknowns: Almost 40% of genes are without a match in functional databases. There is a need for the quantitation of taxonomy and functions expressed by the microbiome. With the metaproteomics datasets we have analyzed here, DIA analysis provides a deeper quantitative insight into the taxonomy and functional features of the microbiome. The DIA approach is reproducible with fewer missing values as compared to the DDA approach. However, there is a need to assess the accuracy of DIA estimations in the context of metaproteomics studies by using benchmarked datasets (such as with known amounts of taxonomy and functions).

Published
2023
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5. The Galaxy platform for accessible, reproducible and collaborative biomedical analyses:2022 update

Author

Afgan, Enis, Nekrutenko, Anton, Grüning, Bjórn A., Blankenberg, Daniel, Goecks, Jeremy, Schatz, Michael C., Ostrovsky, Alexander E., Mahmoud, Alexandru, Lonie, Andrew J., Syme, Anna, Fouilloux, Anne, Bretaudeau, Anthony, Kumar, Anup, Eschenlauer, Arthur C., Desanto, Assunta D., Guerler, Aysam, Serrano-Solano, Beatriz, Batut, Bérénice, Grüning, Björn A., Langhorst, Bradley W., Carr, Bridget, Raubenolt, Bryan A., Hyde, Cameron J., Bromhead, Catherine J., Barnett, Christopher B., Royaux, Coline, Gallardo, Cristóbal, Fornika, Daniel J., Baker, Dannon, Bouvier, Dave, Clements, Dave, De Lima Morais, David A., Tabernero, D. L., Lariviere, Delphine, Nasr, Engy, Zambelli, Federico, Heyl, Florian, Psomopoulos, Fotis, Coppens, Frederik, Price, Gareth R., Cuccuru, Gianmauro, Corguillé, Gildas Le, Von Kuster, Greg, Akbulut, Gulsum Gudukbay, Rasche, Helena, Hans-Rudolf, Hotz, Eguinoa, Ignacio, Makunin, Igor, Ranawaka, Isuru J., Taylor, James P., Joshi, Jayadev, Hillman-Jackson, Jennifer, Chilton, John M., Kamali, Kaivan, Suderman, Keith, Poterlowicz, Krzysztof, Yvan, Le Bras, Lopez-Delisle, Lucille, Sargent, Luke, Bassetti, Madeline E., Tangaro, Marco Antonio, Van Den Beek, Marius, Cech, Martin, Bernt, Matthias, Fahrner, Matthias, Tekman, Mehmet, Föll, Melanie C., Crusoe, Michael R., Roncoroni, Miguel, Kucher, Natalie, Coraor, Nate, Stoler, Nicholas, Rhodes, Nick, Soranzo, Nicola, Pinter, Niko, Goonasekera, Nuwan A., Moreno, Pablo A., Videm, Pavankumar, Melanie, Petera, Mandreoli, Pietro, Jagtap, Pratik D., Gu, Qiang, Weber, Ralf J.M., Lazarus, Ross, Vorderman, Ruben H.P., Hiltemann, Saskia, Golitsynskiy, Sergey, Garg, Shilpa, Bray, Simon A., Gladman, Simon L., Leo, Simone, Mehta, Subina P., Griffin, Timothy J., Jalili, Vahid, Yves, Vandenbrouck, Wen, Victor, Nagampalli, Vijay K., Bacon, Wendi A., De Koning, Willem, Maier, Wolfgang, Briggs, Peter J., Afgan, Enis, Nekrutenko, Anton, Grüning, Bjórn A., Blankenberg, Daniel, Goecks, Jeremy, Schatz, Michael C., Ostrovsky, Alexander E., Mahmoud, Alexandru, Lonie, Andrew J., Syme, Anna, Fouilloux, Anne, Bretaudeau, Anthony, Kumar, Anup, Eschenlauer, Arthur C., Desanto, Assunta D., Guerler, Aysam, Serrano-Solano, Beatriz, Batut, Bérénice, Grüning, Björn A., Langhorst, Bradley W., Carr, Bridget, Raubenolt, Bryan A., Hyde, Cameron J., Bromhead, Catherine J., Barnett, Christopher B., Royaux, Coline, Gallardo, Cristóbal, Fornika, Daniel J., Baker, Dannon, Bouvier, Dave, Clements, Dave, De Lima Morais, David A., Tabernero, D. L., Lariviere, Delphine, Nasr, Engy, Zambelli, Federico, Heyl, Florian, Psomopoulos, Fotis, Coppens, Frederik, Price, Gareth R., Cuccuru, Gianmauro, Corguillé, Gildas Le, Von Kuster, Greg, Akbulut, Gulsum Gudukbay, Rasche, Helena, Hans-Rudolf, Hotz, Eguinoa, Ignacio, Makunin, Igor, Ranawaka, Isuru J., Taylor, James P., Joshi, Jayadev, Hillman-Jackson, Jennifer, Chilton, John M., Kamali, Kaivan, Suderman, Keith, Poterlowicz, Krzysztof, Yvan, Le Bras, Lopez-Delisle, Lucille, Sargent, Luke, Bassetti, Madeline E., Tangaro, Marco Antonio, Van Den Beek, Marius, Cech, Martin, Bernt, Matthias, Fahrner, Matthias, Tekman, Mehmet, Föll, Melanie C., Crusoe, Michael R., Roncoroni, Miguel, Kucher, Natalie, Coraor, Nate, Stoler, Nicholas, Rhodes, Nick, Soranzo, Nicola, Pinter, Niko, Goonasekera, Nuwan A., Moreno, Pablo A., Videm, Pavankumar, Melanie, Petera, Mandreoli, Pietro, Jagtap, Pratik D., Gu, Qiang, Weber, Ralf J.M., Lazarus, Ross, Vorderman, Ruben H.P., Hiltemann, Saskia, Golitsynskiy, Sergey, Garg, Shilpa, Bray, Simon A., Gladman, Simon L., Leo, Simone, Mehta, Subina P., Griffin, Timothy J., Jalili, Vahid, Yves, Vandenbrouck, Wen, Victor, Nagampalli, Vijay K., Bacon, Wendi A., De Koning, Willem, Maier, Wolfgang, and Briggs, Peter J.

Abstract

Galaxy is a mature, browser accessible workbench for scientific computing. It enables scientists to share, analyze and visualize their own data, with minimal technical impediments. A thriving global community continues to use, maintain and contribute to the project, with support from multiple national infrastructure providers that enable freely accessible analysis and training services. The Galaxy Training Network supports free, self-directed, virtual training with >230 integrated tutorials. Project engagement metrics have continued to grow over the last 2 years, including source code contributions, publications, software packages wrapped as tools, registered users and their daily analysis jobs, and new independent specialized servers. Key Galaxy technical developments include an improved user interface for launching large-scale analyses with many files, interactive tools for exploratory data analysis, and a complete suite of machine learning tools. Important scientific developments enabled by Galaxy include Vertebrate Genome Project (VGP) assembly workflows and global SARS-CoV-2 collaborations., Galaxy is a mature, browser accessible workbench for scientific computing. It enables scientists to share, analyze and visualize their own data, with minimal technical impediments. A thriving global community continues to use, maintain and contribute to the project, with support from multiple national infrastructure providers that enable freely accessible analysis and training services. The Galaxy Training Network supports free, self-directed, virtual training with >230 integrated tutorials. Project engagement metrics have continued to grow over the last 2 years, including source code contributions, publications, software packages wrapped as tools, registered users and their daily analysis jobs, and new independent specialized servers. Key Galaxy technical developments include an improved user interface for launching large-scale analyses with many files, interactive tools for exploratory data analysis, and a complete suite of machine learning tools. Important scientific developments enabled by Galaxy include Vertebrate Genome Project (VGP) assembly workflows and global SARS-CoV-2 collaborations.

Published
2022

7. metaQuantome: An Integrated, Quantitative Metaproteomics Approach Reveals Connections Between Taxonomy and Protein Function in Complex Microbiomes*

Author

Easterly, Caleb W., Sajulga, Ray, Mehta, Subina, Johnson, James, Kumar, Praveen, Hubler, Shane, Mesuere, Bart, Rudney, Joel, Griffin, Timothy J., and Jagtap, Pratik D.

Abstract

metaQuantome enables quantitative analysis of the taxonomic and functional state of a microbiome. Leveraging quantitative mass spectrometry data generated from metaproteomic samples along with taxonomic and functional annotations, metaQuantome unravels the complex and hierarchical data structure of taxonomic and functional ontologies. As a result, metaQuantome enables data exploration, tests hypotheses, and generates high-quality visualizations. metaQuantome deciphers the contribution of taxa to a functional process and vice versa. Its accessibility will pave the way for advanced multi-omic analysis of diverse microbiomes.

Published
2019
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8. The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2022 update

Author

Ostrovsky, Alexander E., Mahmoud, Alexandru, Lonie, Andrew J., Syme, Anna, Fouilloux, Anne, Bretaudeau, Anthony, Nekrutenko, Anton, Kumar, Anup, Eschenlauer, Arthur C., DeSanto, Assunta D., Guerler, Aysam, Serrano-Solano, Beatriz, Batut, Berenice, Gruening, Bjoern A., Langhorst, Bradley W., Carr, Bridget, Raubenolt, Bryan A., Hyde, Cameron J., Bromhead, Catherine J., Barnett, Christopher B., Royaux, Coline, Gallardo, Cristobal, Blankenberg, Daniel, Fornika, Daniel J., Baker, Dannon, Bouvier, Dave, Clements, Dave, Morais, David A. de Lima, Tabernero, David Lopez, Lariviere, Delphine, Nasr, Engy, Afgan, Enis, Zambelli, Federico, Heyl, Florian, Psomopoulos, Fotis, Coppens, Frederik, Price, Gareth R., Cuccuru, Gianmauro, Le Corguille, Gildas, Von Kuster, Greg, Akbulut, Gulsum Gudukbay, Rasche, Helena, Hans-Rudolf, Hotz, Eguinoa, Ignacio, Makunin, Igor, Ranawaka, Isuru J., Taylor, James P., Joshi, Jayadev, Hillman-Jackson, Jennifer, Goecks, Jeremy, Chilton, John M., Kamali, Kaivan, Suderman, Keith, Poterlowicz, Krzysztof, Yvan, Le Bras, Lopez-Delisle, Lucille, Sargent, Luke, Bassetti, Madeline E., Tangaro, Marco Antonio, van den Beek, Marius, Cech, Martin, Bernt, Matthias, Fahrner, Matthias, Tekman, Mehmet, Foell, Melanie C., Schatz, Michael C., Crusoe, Michael R., Roncoroni, Miguel, Kucher, Natalie, Coraor, Nate, Stoler, Nicholas, Rhodes, Nick, Soranzo, Nicola, Pinter, Niko, Goonasekera, Nuwan A., Moreno, Pablo A., Videm, Pavankumar, Melanie, Petera, Mandreoli, Pietro, Jagtap, Pratik D., Gu, Qiang, Weber, Ralf J. M., Lazarus, Ross, Vorderman, Ruben H. P., Hiltemann, Saskia, Golitsynskiy, Sergey, Garg, Shilpa, Bray, Simon A., Gladman, Simon L., Leo, Simone, Mehta, Subina P., Griffin, Timothy J., Jalili, Vahid, Yves, Vandenbrouck, Wen, Victor, Nagampalli, Vijay K., Bacon, Wendi A., de Koning, Willem, Maier, Wolfgang, and Briggs, Peter J.

Abstract

Galaxy is a mature, browser accessible workbench for scientific computing. It enables scientists to share, analyze and visualize their own data, with minimal technical impediments. A thriving global community continues to use, maintain and contribute to the project, with support from multiple national infrastructure providers that enable freely accessible analysis and training services. The Galaxy Training Network supports free, self-directed, virtual training with >230 integrated tutorials. Project engagement metrics have continued to grow over the last 2 years, including source code contributions, publications, software packages wrapped as tools, registered users and their daily analysis jobs, and new independent specialized servers. Key Galaxy technical developments include an improved user interface for launching large-scale analyses with many files, interactive tools for exploratory data analysis, and a complete suite of machine learning tools. Important scientific developments enabled by Galaxy include Vertebrate Genome Project (VGP) assembly workflows and global SARS-CoV-2 collaborations.

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