1
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Kupkova K, Mosquera JV, Smith JP, Stolarczyk M, Danehy TL, Lawson JT, Xue B, Stubbs JT, LeRoy N, Sheffield NC. GenomicDistributions: fast analysis of genomic intervals with Bioconductor. BMC Genomics 2022; 23:299. [PMID: 35413804 PMCID: PMC9003978 DOI: 10.1186/s12864-022-08467-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Accepted: 03/13/2022] [Indexed: 11/10/2022] Open
Abstract
Background Epigenome analysis relies on defined sets of genomic regions output by widely used assays such as ChIP-seq and ATAC-seq. Statistical analysis and visualization of genomic region sets is essential to answer biological questions in gene regulation. As the epigenomics community continues generating data, there will be an increasing need for software tools that can efficiently deal with more abundant and larger genomic region sets. Here, we introduce GenomicDistributions, an R package for fast and easy summarization and visualization of genomic region data. Results GenomicDistributions offers a broad selection of functions to calculate properties of genomic region sets, such as feature distances, genomic partition overlaps, and more. GenomicDistributions functions are meticulously optimized for best-in-class speed and generally outperform comparable functions in existing R packages. GenomicDistributions also offers plotting functions that produce editable ggplot objects. All GenomicDistributions functions follow a uniform naming scheme and can handle either single or multiple region set inputs. Conclusions GenomicDistributions offers a fast and scalable tool for exploratory genomic region set analysis and visualization. GenomicDistributions excels in user-friendliness, flexibility of outputs, breadth of functions, and computational performance. GenomicDistributions is available from Bioconductor (https://bioconductor.org/packages/release/bioc/html/GenomicDistributions.html). Supplementary Information The online version contains supplementary material available at 10.1186/s12864-022-08467-y.
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Affiliation(s)
- Kristyna Kupkova
- Center for Public Health Genomics, University of Virginia, Charlottesville, USA.,Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, USA
| | - Jose Verdezoto Mosquera
- Center for Public Health Genomics, University of Virginia, Charlottesville, USA.,Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, USA
| | - Jason P Smith
- Center for Public Health Genomics, University of Virginia, Charlottesville, USA.,Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, USA
| | - Michał Stolarczyk
- Center for Public Health Genomics, University of Virginia, Charlottesville, USA
| | - Tessa L Danehy
- Center for Public Health Genomics, University of Virginia, Charlottesville, USA
| | - John T Lawson
- Center for Public Health Genomics, University of Virginia, Charlottesville, USA.,Department of Biomedical Engineering, University of Virginia, Charlottesville, USA
| | - Bingjie Xue
- Center for Public Health Genomics, University of Virginia, Charlottesville, USA.,Department of Biomedical Engineering, University of Virginia, Charlottesville, USA
| | - John T Stubbs
- Center for Public Health Genomics, University of Virginia, Charlottesville, USA.,Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, USA
| | - Nathan LeRoy
- Center for Public Health Genomics, University of Virginia, Charlottesville, USA.,Department of Biomedical Engineering, University of Virginia, Charlottesville, USA
| | - Nathan C Sheffield
- Center for Public Health Genomics, University of Virginia, Charlottesville, USA. .,Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, USA. .,Department of Biomedical Engineering, University of Virginia, Charlottesville, USA. .,Department of Public Health Sciences, University of Virginia, Charlottesville, USA.
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2
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Carey MA, Medlock GL, Stolarczyk M, Petri WA, Guler JL, Papin JA. Comparative analyses of parasites with a comprehensive database of genome-scale metabolic models. PLoS Comput Biol 2022; 18:e1009870. [PMID: 35196325 PMCID: PMC8901074 DOI: 10.1371/journal.pcbi.1009870] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Revised: 03/07/2022] [Accepted: 01/27/2022] [Indexed: 01/01/2023] Open
Abstract
Protozoan parasites cause diverse diseases with large global impacts. Research on the pathogenesis and biology of these organisms is limited by economic and experimental constraints. Accordingly, studies of one parasite are frequently extrapolated to infer knowledge about another parasite, across and within genera. Model in vitro or in vivo systems are frequently used to enhance experimental manipulability, but these systems generally use species related to, yet distinct from, the clinically relevant causal pathogen. Characterization of functional differences among parasite species is confined to post hoc or single target studies, limiting the utility of this extrapolation approach. To address this challenge and to accelerate parasitology research broadly, we present a functional comparative analysis of 192 genomes, representing every high-quality, publicly-available protozoan parasite genome including Plasmodium, Toxoplasma, Cryptosporidium, Entamoeba, Trypanosoma, Leishmania, Giardia, and other species. We generated an automated metabolic network reconstruction pipeline optimized for eukaryotic organisms. These metabolic network reconstructions serve as biochemical knowledgebases for each parasite, enabling qualitative and quantitative comparisons of metabolic behavior across parasites. We identified putative differences in gene essentiality and pathway utilization to facilitate the comparison of experimental findings and discovered that phylogeny is not the sole predictor of metabolic similarity. This knowledgebase represents the largest collection of genome-scale metabolic models for both pathogens and eukaryotes; with this resource, we can predict species-specific functions, contextualize experimental results, and optimize selection of experimental systems for fastidious species.
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Affiliation(s)
- Maureen A. Carey
- Department of Microbiology, Immunology, and Cancer Biology, University of Virginia School of Medicine, Charlottesville, Virginia, United States of America
- Division of Infectious Diseases and International Health, Department of Medicine, University of Virginia School of Medicine, Charlottesville, Virginia, United States of America
- * E-mail: (MAC); (JP)
| | - Gregory L. Medlock
- Department of Biomedical Engineering, University of Virginia School of Medicine, Charlottesville, Virginia, United States of America
| | - Michał Stolarczyk
- Department of Biology, University of Virginia, Charlottesville, Virginia, United States of America
- Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, Virginia, United States of America
| | - William A. Petri
- Division of Infectious Diseases and International Health, Department of Medicine, University of Virginia School of Medicine, Charlottesville, Virginia, United States of America
| | - Jennifer L. Guler
- Division of Infectious Diseases and International Health, Department of Medicine, University of Virginia School of Medicine, Charlottesville, Virginia, United States of America
- Department of Biology, University of Virginia, Charlottesville, Virginia, United States of America
| | - Jason A. Papin
- Division of Infectious Diseases and International Health, Department of Medicine, University of Virginia School of Medicine, Charlottesville, Virginia, United States of America
- Department of Biomedical Engineering, University of Virginia School of Medicine, Charlottesville, Virginia, United States of America
- Department of Biochemistry & Molecular Genetics, University of Virginia School of Medicine, Charlottesville, Virginia, United States of America
- * E-mail: (MAC); (JP)
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3
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VijayKrishna N, Joshi J, Coraor N, Hillman-Jackson J, Bouvier D, van den Beek M, Eguinoa I, Coppens F, Davis J, Stolarczyk M, Sheffield NC, Gladman S, Cuccuru G, Grüning B, Soranzo N, Rasche H, Langhorst BW, Bernt M, Fornika D, de Lima Morais DA, Barrette M, van Heusden P, Petrillo M, Puertas-Gallardo A, Patak A, Hotz HR, Blankenberg D. Expanding the Galaxy's reference data. Bioinform Adv 2022; 2:vbac030. [PMID: 35669346 PMCID: PMC9155181 DOI: 10.1093/bioadv/vbac030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/12/2021] [Revised: 04/01/2022] [Accepted: 04/26/2022] [Indexed: 01/27/2023]
Abstract
Summary Properly and effectively managing reference datasets is an important task for many bioinformatics analyses. Refgenie is a reference asset management system that allows users to easily organize, retrieve and share such datasets. Here, we describe the integration of refgenie into the Galaxy platform. Server administrators are able to configure Galaxy to make use of reference datasets made available on a refgenie instance. In addition, a Galaxy Data Manager tool has been developed to provide a graphical interface to refgenie's remote reference retrieval functionality. A large collection of reference datasets has also been made available using the CVMFS (CernVM File System) repository from GalaxyProject.org, with mirrors across the USA, Canada, Europe and Australia, enabling easy use outside of Galaxy. Availability and implementation The ability of Galaxy to use refgenie assets was added to the core Galaxy framework in version 22.01, which is available from https://github.com/galaxyproject/galaxy under the Academic Free License version 3.0. The refgenie Data Manager tool can be installed via the Galaxy ToolShed, with source code managed at https://github.com/BlankenbergLab/galaxy-tools-blankenberg/tree/main/data_managers/data_manager_refgenie_pull and released using an MIT license. Access to existing data is also available through CVMFS, with instructions at https://galaxyproject.org/admin/reference-data-repo/. No new data were generated or analyzed in support of this research.
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Affiliation(s)
| | - Jayadev Joshi
- Genomic Medicine Institute, Cleveland Clinic, Cleveland, OH 44195, USA
| | - Nate Coraor
- Department of Biochemistry and Molecular Biology, Penn State University, University Park, PA 16802, USA
| | - Jennifer Hillman-Jackson
- Department of Biochemistry and Molecular Biology, Penn State University, University Park, PA 16802, USA
| | - Dave Bouvier
- Department of Biochemistry and Molecular Biology, Penn State University, University Park, PA 16802, USA
| | - Marius van den Beek
- Department of Biochemistry and Molecular Biology, Penn State University, University Park, PA 16802, USA
| | - Ignacio Eguinoa
- VIB Center for Plant Systems Biology, 9052 Ghent, Belgium
- Department of Plant Biotechnology and Bioinformatics, Ghent University, 9052 Ghent, Belgium
| | - Frederik Coppens
- VIB Center for Plant Systems Biology, 9052 Ghent, Belgium
- Department of Plant Biotechnology and Bioinformatics, Ghent University, 9052 Ghent, Belgium
| | - John Davis
- Department of Biology, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Michał Stolarczyk
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22903, USA
| | - Nathan C Sheffield
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22903, USA
| | | | | | - Björn Grüning
- University of Freiburg, Freiburg im Breisgau, Germany
| | | | - Helena Rasche
- Clinical Bioinformatics Group, Department of Pathology, Erasmus Medical Center, 3015 CN Rotterdam, The Netherlands
| | | | - Matthias Bernt
- Department Computational Biology, Helmholtz Centre for Environmental Research, UFZ, 04318 Leipzig, Germany
| | - Dan Fornika
- BC Centre for Disease Control Public Health Laboratory, Vancouver, BC, Canada
| | | | - Michel Barrette
- Centre de Calcul Scientifique, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Peter van Heusden
- South African Medical Research Council Bioinformatics Unit, South African National Bioinformatics Institute, University of the Western Cape, Bellville, South Africa
| | - Mauro Petrillo
- European Commission, Joint Research Centre (JRC), Ispra, Italy
| | | | - Alex Patak
- European Commission, Joint Research Centre (JRC), Ispra, Italy
| | - Hans-Rudolf Hotz
- Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland
- SIB Swiss Institute of Bioinformatics, Basel, Switzerland
| | - Daniel Blankenberg
- Genomic Medicine Institute, Cleveland Clinic, Cleveland, OH 44195, USA
- Department of Molecular Medicine, Cleveland Clinic Lerner College of Medicine, Case Western Reserve University, Cleveland, OH 44195, USA
- To whom correspondence should be addressed.
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4
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Sheffield NC, Stolarczyk M, Reuter VP, Rendeiro AF. Linking big biomedical datasets to modular analysis with Portable Encapsulated Projects. Gigascience 2021; 10:6454632. [PMID: 34890448 PMCID: PMC8673555 DOI: 10.1093/gigascience/giab077] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Revised: 04/20/2021] [Accepted: 11/04/2021] [Indexed: 12/26/2022] Open
Abstract
Background Organizing and annotating biological sample data is critical in data-intensive bioinformatics. Unfortunately, metadata formats from a data provider are often incompatible with requirements of a processing tool. There is no broadly accepted standard to organize metadata across biological projects and bioinformatics tools, restricting the portability and reusability of both annotated datasets and analysis software. Results To address this, we present the Portable Encapsulated Project (PEP) specification, a formal specification for biological sample metadata structure. The PEP specification accommodates typical features of data-intensive bioinformatics projects with many biological samples. In addition to standardization, the PEP specification provides descriptors and modifiers for project-level and sample-level metadata, which improve portability across both computing environments and data processing tools. PEPs include a schema validator framework, allowing formal definition of required metadata attributes for data analysis broadly. We have implemented packages for reading PEPs in both Python and R to provide a language-agnostic interface for organizing project metadata. Conclusions The PEP specification is an important step toward unifying data annotation and processing tools in data-intensive biological research projects. Links to tools and documentation are available at http://pep.databio.org/.
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Affiliation(s)
- Nathan C Sheffield
- Center for Public Health Genomics, University of Virginia, VA 22908, USA.,Department of Public Health Sciences, University of Virginia, VA 22908, USA.,Department of Biomedical Engineering, University of Virginia, VA 22908, USA.,Department of Biochemistry and Molecular Genetics, University of Virginia, VA 22908, USA
| | - Michał Stolarczyk
- Center for Public Health Genomics, University of Virginia, VA 22908, USA
| | - Vincent P Reuter
- Center for Public Health Genomics, University of Virginia, VA 22908, USA.,Genomics and Computational Biology Graduate Group, University of Pennsylvania, PA 19087, USA
| | - André F Rendeiro
- Institute for Computational Biomedicine, Weill Cornell Medical College, NY 10021, USA.,Caryl and Israel Englander Institute for Precision Medicine, Weill Cornell Medical College, NY 10021, USA
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5
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Stolarczyk M, Xue B, Sheffield NC. Identity and compatibility of reference genome resources. NAR Genom Bioinform 2021; 3:lqab036. [PMID: 34017945 PMCID: PMC8121092 DOI: 10.1093/nargab/lqab036] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2021] [Revised: 03/10/2021] [Accepted: 04/22/2021] [Indexed: 11/14/2022] Open
Abstract
Genome analysis relies on reference data like sequences, feature annotations, and aligner indexes. These data can be found in many versions from many sources, making it challenging to identify and assess compatibility among them. For example, how can you determine which indexes are derived from identical raw sequence files, or which annotations share a compatible coordinate system? Here, we describe a novel approach to establish identity and compatibility of reference genome resources. We approach this with three advances: first, we derive unique identifiers for each resource; second, we record parent-child relationships among resources; and third, we describe recursive identifiers that determine identity as well as compatibility of coordinate systems and sequence names. These advances facilitate portability, reproducibility, and re-use of genome reference data. Available athttps://refgenie.databio.org.
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Affiliation(s)
- Michał Stolarczyk
- Center for Public Health Genomics, University of Virginia, Virginia, 22908, USA
| | - Bingjie Xue
- Center for Public Health Genomics, University of Virginia, Virginia, 22908, USA
| | - Nathan C Sheffield
- Center for Public Health Genomics, University of Virginia, Virginia, 22908, USA
- Department of Public Health Sciences, University of Virginia, Virginia, 22908, USA
- Department of Biomedical Engineering, University of Virginia, Virginia, 22904, USA
- Department of Biochemistry and Molecular Genetics, University of Virginia, Virginia, 22908, USA
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6
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Stolarczyk M, Reuter VP, Smith JP, Magee NE, Sheffield NC. Refgenie: a reference genome resource manager. Gigascience 2020; 9:giz149. [PMID: 31995185 PMCID: PMC6988606 DOI: 10.1093/gigascience/giz149] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2019] [Revised: 10/22/2019] [Accepted: 11/19/2019] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND Reference genome assemblies are essential for high-throughput sequencing analysis projects. Typically, genome assemblies are stored on disk alongside related resources; e.g., many sequence aligners require the assembly to be indexed. The resulting indexes are broadly applicable for downstream analysis, so it makes sense to share them. However, there is no simple tool to do this. RESULTS Here, we introduce refgenie, a reference genome assembly asset manager. Refgenie makes it easier to organize, retrieve, and share genome analysis resources. In addition to genome indexes, refgenie can manage any files related to reference genomes, including sequences and annotation files. Refgenie includes a command line interface and a server application that provides a RESTful API, so it is useful for both tool development and analysis. CONCLUSIONS Refgenie streamlines sharing genome analysis resources among groups and across computing environments. Refgenie is available at https://refgenie.databio.org.
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Affiliation(s)
- Michał Stolarczyk
- Center for Public Health Genomics, University of Virginia, PO Box 800717, Charlottesville, VA, 22908, USA
| | - Vincent P Reuter
- Center for Public Health Genomics, University of Virginia, PO Box 800717, Charlottesville, VA, 22908, USA
| | - Jason P Smith
- Center for Public Health Genomics, University of Virginia, PO Box 800717, Charlottesville, VA, 22908, USA
- Department of Biochemistry and Molecular Genetics, University of Virginia, PO Box 800733, Charlottesville, VA, 22908, USA
| | - Neal E Magee
- Research Computing, University of Virginia, 560 Ray C. Hunt Drive, Charlottesville, VA, 22903, USA
| | - Nathan C Sheffield
- Center for Public Health Genomics, University of Virginia, PO Box 800717, Charlottesville, VA, 22908, USA
- Department of Biochemistry and Molecular Genetics, University of Virginia, PO Box 800733, Charlottesville, VA, 22908, USA
- Department of Public Health Sciences, University of Virginia, PO Box 800717, Charlottesville, VA, 22908, USA
- Department of Biomedical Engineering, University of Virginia, PO Box 400259, Charlottesville, VA, 22904, USA
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7
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Roider T, Frauhammer F, Seufert J, Bordas M, Stolarczyk M, Rabe S, Malm J, Bruch P, Hundemer M, Rippe K, Goeppert B, Seiffert M, Brors B, Mechtersheimer G, Müller-Tidow C, Fröhling S, Schlesner M, Huber W, Anders S, Dietrich S. TRANSCRIPTIONAL AND GENOMIC INTRA-TUMOR HETEROGENEITY DRIVES SUBCLONE SPECIFIC DRUG RESPONSES IN DIFFUSE LARGE B CELL LYMPHOMA. Hematol Oncol 2019. [DOI: 10.1002/hon.45_2629] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Affiliation(s)
- T. Roider
- Department of Medicine V; Hematology, Oncology and Rheumatology, University of Heidelberg; Heidelberg Germany
| | - F. Frauhammer
- Centre for Molecular Biology; University of Heidelberg; Heidelberg Germany
| | - J. Seufert
- Bioinformatics and Omics Data Analytics; German Cancer Research Center (DKFZ); Heidelberg Germany
| | - M. Bordas
- Department of Molecular Genetics; German Cancer Research Center (DKFZ); Heidelberg Germany
| | - M. Stolarczyk
- Department of Medicine V; Hematology, Oncology and Rheumatology, University of Heidelberg; Heidelberg Germany
| | - S. Rabe
- Department of Medicine V; Hematology, Oncology and Rheumatology, University of Heidelberg; Heidelberg Germany
| | - J. Malm
- Division of Chromatin Networks; German Cancer Research Center (DKFZ) and Bioquant; Heidelberg Germany
| | - P. Bruch
- Department of Medicine V; Hematology, Oncology and Rheumatology, University of Heidelberg; Heidelberg Germany
| | - M. Hundemer
- Department of Medicine V; Hematology, Oncology and Rheumatology, University of Heidelberg; Heidelberg Germany
| | - K. Rippe
- Division of Chromatin Networks; German Cancer Research Center (DKFZ) and Bioquant; Heidelberg Germany
| | - B. Goeppert
- Institute of Pathology; University of Heidelberg; Heidelberg Germany
| | - M. Seiffert
- Department of Molecular Genetics; German Cancer Research Center (DKFZ); Heidelberg Germany
| | - B. Brors
- Bioinformatics and Omics Data Analytics; German Cancer Research Center (DKFZ); Heidelberg Germany
| | - G. Mechtersheimer
- Institute of Pathology; University of Heidelberg; Heidelberg Germany
| | - C. Müller-Tidow
- Department of Medicine V; Hematology, Oncology and Rheumatology, University of Heidelberg; Heidelberg Germany
| | - S. Fröhling
- Translational Oncology; National Center for Tumor Diseases (NCT); Heidelberg Germany
| | - M. Schlesner
- Bioinformatics and Omics Data Analytics; German Cancer Research Center (DKFZ); Heidelberg Germany
| | - W. Huber
- Genome Biology; European Molecular Biology Laboratory (EMBL); Heidelberg Germany
| | - S. Anders
- Centre for Molecular Biology; University of Heidelberg; Heidelberg Germany
| | - S. Dietrich
- Department of Medicine V; Hematology, Oncology and Rheumatology, University of Heidelberg; Heidelberg Germany
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8
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Płuciennik A, Stolarczyk M, Bzówka M, Raczyńska A, Magdziarz T, Góra A. BALCONY: an R package for MSA and functional compartments of protein variability analysis. BMC Bioinformatics 2018; 19:300. [PMID: 30107777 PMCID: PMC6092823 DOI: 10.1186/s12859-018-2294-z] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2018] [Accepted: 07/23/2018] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND Here, we present an R package for entropy/variability analysis that facilitates prompt and convenient data extraction, manipulation and visualization of protein features from multiple sequence alignments. BALCONY can work with residues dispersed across a protein sequence and map them on the corresponding alignment of homologous protein sequences. Additionally, it provides several entropy and variability scores that indicate the conservation of each residue. RESULTS Our package allows the user to visualize evolutionary variability by locating the positions most likely to vary and to assess mutation candidates in protein engineering. CONCLUSION In comparison to other R packages BALCONY allows conservation/variability analysis in context of protein structure with linkage of the appropriate metrics with physicochemical features of user choice. AVAILABILITY CRAN project page: https://cran.r-project.org/package=BALCONY and our website: http://www.tunnelinggroup.pl/software/ for major platforms: Linux/Unix, Windows and Mac OS X.
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Affiliation(s)
- Alicja Płuciennik
- Tunneling Group, Biotechnology Centre, Silesian University of Technology, ul. Krzywoustego 8, 44-100, Gliwice, Poland.,Institute of Automatic Control, Silesian University of Technology, Akademicka 16, 44-100, Gliwice, Poland
| | - Michał Stolarczyk
- Tunneling Group, Biotechnology Centre, Silesian University of Technology, ul. Krzywoustego 8, 44-100, Gliwice, Poland.,Institute of Automatic Control, Silesian University of Technology, Akademicka 16, 44-100, Gliwice, Poland
| | - Maria Bzówka
- Tunneling Group, Biotechnology Centre, Silesian University of Technology, ul. Krzywoustego 8, 44-100, Gliwice, Poland.,Faculty of Chemistry, Silesian University of Technology, ks. Marcina Strzody 9, 44-100, Gliwice, Poland
| | - Agata Raczyńska
- Tunneling Group, Biotechnology Centre, Silesian University of Technology, ul. Krzywoustego 8, 44-100, Gliwice, Poland.,Institute of Automatic Control, Silesian University of Technology, Akademicka 16, 44-100, Gliwice, Poland
| | - Tomasz Magdziarz
- Tunneling Group, Biotechnology Centre, Silesian University of Technology, ul. Krzywoustego 8, 44-100, Gliwice, Poland
| | - Artur Góra
- Tunneling Group, Biotechnology Centre, Silesian University of Technology, ul. Krzywoustego 8, 44-100, Gliwice, Poland.
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9
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Maślanka A, Krzek J, Żuromska B, Stolarczyk M. Identification and determination of compounds belonging to the group of OUN pharmaceutical agents by thin-layer chromatography with densitometric detection in biological material. ACTA CHROMATOGR 2011. [DOI: 10.1556/achrom.23.2011.2.5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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10
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Rzeszutko W, Stolarczyk M, Apola A. [Determination of iodide ions content in the edible salts and medical preparations by spectrophotometric and voltamperometric methods]. Rocz Panstw Zakl Hig 1999; 50:139-44. [PMID: 10523932] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/14/2023] Open
Abstract
In this paper the spectrophotometric and voltamperometric methods for the determination of the iodide ions content are presented. The conformity of the edible table salts iodisation to the Polish Standards and to the contests declared by the producer was verified.
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Affiliation(s)
- W Rzeszutko
- Katedra Chemii Nieorganicznej i Analitycznej Collegium Medicum Uniwersytetu Jagiellońskiego, Kraków
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