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Journal articles on the topic 'Genomics workflow'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

John, Aji, Kathleen Muenzen, and Kristiina Ausmees. "Evaluation of serverless computing for scalable execution of a joint variant calling workflow." PLOS ONE 16, no. 7 (2021): e0254363. http://dx.doi.org/10.1371/journal.pone.0254363.

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Advances in whole-genome sequencing have greatly reduced the cost and time of obtaining raw genetic information, but the computational requirements of analysis remain a challenge. Serverless computing has emerged as an alternative to using dedicated compute resources, but its utility has not been widely evaluated for standardized genomic workflows. In this study, we define and execute a best-practice joint variant calling workflow using the SWEEP workflow management system. We present an analysis of performance and scalability, and discuss the utility of the serverless paradigm for executing w

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Diamond, Joel. "Genomics Within the Clinical Workflow." Oncology Times 40, no. 18 (2018): 13. http://dx.doi.org/10.1097/01.cot.0000546351.05658.8b.

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Carey, Vincent J., Marcel Ramos, Benjamin J. Stubbs, et al. "Global Alliance for Genomics and Health Meets Bioconductor: Toward Reproducible and Agile Cancer Genomics at Cloud Scale." JCO Clinical Cancer Informatics, no. 4 (September 2020): 472–79. http://dx.doi.org/10.1200/cci.19.00111.

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PURPOSE Institutional efforts toward the democratization of cloud-scale data and analysis methods for cancer genomics are proceeding rapidly. As part of this effort, we bridge two major bioinformatic initiatives: the Global Alliance for Genomics and Health (GA4GH) and Bioconductor. METHODS We describe in detail a use case in pancancer transcriptomics conducted by blending implementations of the GA4GH Workflow Execution Services and Tool Registry Service concepts with the Bioconductor curatedTCGAData and BiocOncoTK packages. RESULTS We carried out the analysis with a formally archived workflow

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Khvorykh, Gennady, Andrey Khrunin, Ivan Filippenkov, Vasily Stavchansky, Lyudmila Dergunova, and Svetlana Limborska. "A Workflow for Selection of Single Nucleotide Polymorphic Markers for Studying of Genetics of Ischemic Stroke Outcomes." Genes 12, no. 3 (2021): 328. http://dx.doi.org/10.3390/genes12030328.

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In this paper we propose a workflow for studying the genetic architecture of ischemic stroke outcomes. It develops further the candidate gene approach. The workflow is based on the animal model of brain ischemia, comparative genomics, human genomic variations, and algorithms of selection of tagging single nucleotide polymorphisms (tagSNPs) in genes which expression was changed after ischemic stroke. The workflow starts from a set of rat genes that changed their expression in response to brain ischemia and results in a set of tagSNPs, which represent other SNPs in the human genes analyzed and i

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Kulchak Rahm, Alanna, Nephi A. Walton, Lynn K. Feldman, et al. "User testing of a diagnostic decision support system with machine-assisted chart review to facilitate clinical genomic diagnosis." BMJ Health & Care Informatics 28, no. 1 (2021): e100331. http://dx.doi.org/10.1136/bmjhci-2021-100331.

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ObjectivesThere is a need in clinical genomics for systems that assist in clinical diagnosis, analysis of genomic information and periodic reanalysis of results, and can use information from the electronic health record to do so. Such systems should be built using the concepts of human-centred design, fit within clinical workflows and provide solutions to priority problems.MethodsWe adapted a commercially available diagnostic decision support system (DDSS) to use extracted findings from a patient record and combine them with genomic variant information in the DDSS interface. Three representati

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Ukmar, G., G. E. M. Melloni, L. Raddrizzani, et al. "PATRI, a Genomics Data Integration Tool for Biomarker Discovery." BioMed Research International 2018 (June 28, 2018): 1–13. http://dx.doi.org/10.1155/2018/2012078.

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The availability of genomic datasets in association with clinical, phenotypic, and drug sensitivity information represents an invaluable source for potential therapeutic applications, supporting the identification of new drug sensitivity biomarkers and pharmacological targets. Drug discovery and precision oncology can largely benefit from the integration of treatment molecular discriminants obtained from cell line models and clinical tumor samples; however this task demands comprehensive analysis approaches for the discovery of underlying data connections. Here we introduce PATRI (Platform for

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Silva, Tiago C., Antonio Colaprico, Catharina Olsen, et al. "TCGA Workflow: Analyze cancer genomics and epigenomics data using Bioconductor packages." F1000Research 5 (June 29, 2016): 1542. http://dx.doi.org/10.12688/f1000research.8923.1.

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Biotechnological advances in sequencing have led to an explosion of publicly available data via large international consortia such as The Cancer Genome Atlas (TCGA), The Encyclopedia of DNA Elements (ENCODE), and The NIH Roadmap Epigenomics Mapping Consortium (Roadmap). These projects have provided unprecedented opportunities to interrogate the epigenome of cultured cancer cell lines as well as normal and tumor tissues with high genomic resolution. The bioconductor project offers more than 1,000 open-source software and statistical packages to analyze high-throughput genomic data. However, mos

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Silva, Tiago C., Antonio Colaprico, Catharina Olsen, et al. "TCGA Workflow: Analyze cancer genomics and epigenomics data using Bioconductor packages." F1000Research 5 (December 28, 2016): 1542. http://dx.doi.org/10.12688/f1000research.8923.2.

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Biotechnological advances in sequencing have led to an explosion of publicly available data via large international consortia such as The Cancer Genome Atlas (TCGA), The Encyclopedia of DNA Elements (ENCODE), and The NIH Roadmap Epigenomics Mapping Consortium (Roadmap). These projects have provided unprecedented opportunities to interrogate the epigenome of cultured cancer cell lines as well as normal and tumor tissues with high genomic resolution. The Bioconductor project offers more than 1,000 open-source software and statistical packages to analyze high-throughput genomic data. However, mos

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Rossetto, Maurizio, Jia-Yee Samantha Yap, Jedda Lemmon, et al. "A conservation genomics workflow to guide practical management actions." Global Ecology and Conservation 26 (April 2021): e01492. http://dx.doi.org/10.1016/j.gecco.2021.e01492.

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Ahmed, Azza E., Phelelani T. Mpangase, Sumir Panji, et al. "Organizing and running bioinformatics hackathons within Africa: The H3ABioNet cloud computing experience." AAS Open Research 1 (April 18, 2018): 9. http://dx.doi.org/10.12688/aasopenres.12847.1.

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The need for portable and reproducible genomics analysis pipelines is growing globally as well as in Africa, especially with the growth of collaborative projects like the Human Health and Heredity in Africa Consortium (H3Africa). The Pan-African H3Africa Bioinformatics Network (H3ABioNet) recognized the need for portable, reproducible pipelines adapted to heterogeneous compute environments, and for the nurturing of technical expertise in workflow languages and containerization technologies. To address this need, in 2016 H3ABioNet arranged its first Cloud Computing and Reproducible Workflows Ha

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Ahmed, Azza E., Phelelani T. Mpangase, Sumir Panji, et al. "Organizing and running bioinformatics hackathons within Africa: The H3ABioNet cloud computing experience." AAS Open Research 1 (August 7, 2019): 9. http://dx.doi.org/10.12688/aasopenres.12847.2.

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The need for portable and reproducible genomics analysis pipelines is growing globally as well as in Africa, especially with the growth of collaborative projects like the Human Health and Heredity in Africa Consortium (H3Africa). The Pan-African H3Africa Bioinformatics Network (H3ABioNet) recognized the need for portable, reproducible pipelines adapted to heterogeneous computing environments, and for the nurturing of technical expertise in workflow languages and containerization technologies. Building on the network’s Standard Operating Procedures (SOPs) for common genomic analyses, H3ABioNet

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Cheung, M. K., and H. S. Kwan. "Fighting Outbreaks with Bacterial Genomics: Case Review and Workflow Proposal." Public Health Genomics 15, no. 6 (2012): 341–51. http://dx.doi.org/10.1159/000342770.

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Cribbs, Adam P., Sebastian Luna-Valero, Charlotte George, et al. "CGAT-core: a python framework for building scalable, reproducible computational biology workflows." F1000Research 8 (April 4, 2019): 377. http://dx.doi.org/10.12688/f1000research.18674.1.

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In the genomics era computational biologists regularly need to process, analyse and integrate large and complex biomedical datasets. Analysis inevitably involves multiple dependent steps, resulting in complex pipelines or workflows, often with several branches. Large data volumes mean that processing needs to be quick and efficient and scientific rigour requires that analysis be consistent and fully reproducible. We have developed CGAT-core, a python package for the rapid construction of complex computational workflows. CGAT-core seamlessly handles parallelisation across high performance compu

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Cribbs, Adam P., Sebastian Luna-Valero, Charlotte George, et al. "CGAT-core: a python framework for building scalable, reproducible computational biology workflows." F1000Research 8 (July 16, 2019): 377. http://dx.doi.org/10.12688/f1000research.18674.2.

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In the genomics era computational biologists regularly need to process, analyse and integrate large and complex biomedical datasets. Analysis inevitably involves multiple dependent steps, resulting in complex pipelines or workflows, often with several branches. Large data volumes mean that processing needs to be quick and efficient and scientific rigour requires that analysis be consistent and fully reproducible. We have developed CGAT-core, a python package for the rapid construction of complex computational workflows. CGAT-core seamlessly handles parallelisation across high performance compu

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Ma, Xiaoxia, Yijun Meng, Pu Wang, Zhonghai Tang, Huizhong Wang, and Tian Xie. "Bioinformatics-assisted, integrated omics studies on medicinal plants." Briefings in Bioinformatics 21, no. 6 (2019): 1857–74. http://dx.doi.org/10.1093/bib/bbz132.

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Abstract The immense therapeutic and economic values of medicinal plants have attracted increasing attention from the worldwide researchers. It has been recognized that production of the authentic and high-quality herbal drugs became the prerequisite for maintaining the healthy development of the traditional medicine industry. To this end, intensive research efforts have been devoted to the basic studies, in order to pave a way for standardized authentication of the plant materials, and bioengineering of the metabolic pathways in the medicinal plants. In this paper, the recent advances of omic

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Tinelli, Andrea, Roberta Martignago, Daniele Vergara, Giuseppe Leo, Antonio Malvasi, and Raffaele Tinelli. "Endometriosis Management: Workflow on Genomics and Proteomics and Future Biomolecular Pharmacotherapy." Current Medicinal Chemistry 15, no. 21 (2008): 2099–107. http://dx.doi.org/10.2174/092986708785747571.

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Yu, Bin, and Karl Kumbier. "Veridical data science." Proceedings of the National Academy of Sciences 117, no. 8 (2020): 3920–29. http://dx.doi.org/10.1073/pnas.1901326117.

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Building and expanding on principles of statistics, machine learning, and scientific inquiry, we propose the predictability, computability, and stability (PCS) framework for veridical data science. Our framework, composed of both a workflow and documentation, aims to provide responsible, reliable, reproducible, and transparent results across the data science life cycle. The PCS workflow uses predictability as a reality check and considers the importance of computation in data collection/storage and algorithm design. It augments predictability and computability with an overarching stability pri

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Romano, P., G. Bertolini, F. De Paoli, et al. "Network integration of data and analysis of oncology interest." Journal of Integrative Bioinformatics 3, no. 1 (2006): 45–55. http://dx.doi.org/10.1515/jib-2006-21.

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Summary The Human Genome Project has deeply transformed biology and the field has since then expanded to the management, processing, analysis and visualization of large quantities of data from genomics, proteomics, medicinal chemistry and drug screening. This huge amount of data and the heterogeneity of software tools that are used implies the adoption on a very large scale of new, flexible tools that can enable researchers to integrate data and analysis on the network. ICT technology standards and tools, like Web Services and related languages, and workflow management systems, can support the

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Ocaña, Kary A. C. S., Daniel de Oliveira, Jonas Dias, Eduardo Ogasawara, and Marta Mattoso. "Designing a parallel cloud based comparative genomics workflow to improve phylogenetic analyses." Future Generation Computer Systems 29, no. 8 (2013): 2205–19. http://dx.doi.org/10.1016/j.future.2013.04.005.

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Conway, Jake R., Jeremy L. Warner, Wendy S. Rubinstein, and Robert S. Miller. "Next-Generation Sequencing and the Clinical Oncology Workflow: Data Challenges, Proposed Solutions, and a Call to Action." JCO Precision Oncology, no. 3 (December 2019): 1–10. http://dx.doi.org/10.1200/po.19.00232.

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PURPOSE Next-generation sequencing (NGS) of tumor and germline DNA is foundational for precision oncology, with rapidly expanding diagnostic, prognostic, and therapeutic implications. Although few question the importance of NGS in modern oncology care, the process of gathering primary molecular data, integrating it into electronic health records, and optimally using it as part of a clinical workflow remains far from seamless. Numerous challenges persist around data standards and interoperability, and clinicians frequently face difficulties in managing the growing amount of genomic knowledge re

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Ramsey, Jolene, Helena Rasche, Cory Maughmer, et al. "Galaxy and Apollo as a biologist-friendly interface for high-quality cooperative phage genome annotation." PLOS Computational Biology 16, no. 11 (2020): e1008214. http://dx.doi.org/10.1371/journal.pcbi.1008214.

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In the modern genomic era, scientists without extensive bioinformatic training need to apply high-power computational analyses to critical tasks like phage genome annotation. At the Center for Phage Technology (CPT), we developed a suite of phage-oriented tools housed in open, user-friendly web-based interfaces. A Galaxy platform conducts computationally intensive analyses and Apollo, a collaborative genome annotation editor, visualizes the results of these analyses. The collection includes open source applications such as the BLAST+ suite, InterProScan, and several gene callers, as well as un

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Mondelli, Maria Luiza, Thiago Magalhães, Guilherme Loss, et al. "BioWorkbench: a high-performance framework for managing and analyzing bioinformatics experiments." PeerJ 6 (August 29, 2018): e5551. http://dx.doi.org/10.7717/peerj.5551.

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Advances in sequencing techniques have led to exponential growth in biological data, demanding the development of large-scale bioinformatics experiments. Because these experiments are computation- and data-intensive, they require high-performance computing techniques and can benefit from specialized technologies such as Scientific Workflow Management Systems and databases. In this work, we present BioWorkbench, a framework for managing and analyzing bioinformatics experiments. This framework automatically collects provenance data, including both performance data from workflow execution and dat

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Lynch, Tarah, Aaron Petkau, Natalie Knox, Morag Graham, and Gary Van Domselaar. "A Primer on Infectious Disease Bacterial Genomics." Clinical Microbiology Reviews 29, no. 4 (2016): 881–913. http://dx.doi.org/10.1128/cmr.00001-16.

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SUMMARYThe number of large-scale genomics projects is increasing due to the availability of affordable high-throughput sequencing (HTS) technologies. The use of HTS for bacterial infectious disease research is attractive because one whole-genome sequencing (WGS) run can replace multiple assays for bacterial typing, molecular epidemiology investigations, and more in-depth pathogenomic studies. The computational resources and bioinformatics expertise required to accommodate and analyze the large amounts of data pose new challenges for researchers embarking on genomics projects for the first time

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LIMAYE, BHAKTI, RUMA BANERJEE, AVIK DATTA, et al. "ANVAYA: A WORKFLOWS ENVIRONMENT FOR AUTOMATED GENOME ANALYSIS." Journal of Bioinformatics and Computational Biology 10, no. 04 (2012): 1250006. http://dx.doi.org/10.1142/s0219720012500060.

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Anvaya is a workflow environment for automated genome analysis that provides an interface for several bioinformatics tools and databases, loosely coupled together in a coordinated system, enabling the execution of a set of analyses tools in series or in parallel. It is a client-server workflow environment that has an advantage over existing software as it enables extensive pre & post processing of biological data in an efficient manner. "Anvaya" offers the user, novel functionalities to carry out exhaustive comparative analysis via "custom tools," which are tools with new functionality not

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Nestor, Jordan G., Maddalena Marasa, Hila Milo-Rasouly, et al. "Pilot Study of Return of Genetic Results to Patients in Adult Nephrology." Clinical Journal of the American Society of Nephrology 15, no. 5 (2020): 651–64. http://dx.doi.org/10.2215/cjn.12481019.

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Background and objectivesActionable genetic findings have implications for care of patients with kidney disease, and genetic testing is an emerging tool in nephrology practice. However, there are scarce data regarding best practices for return of results and clinical application of actionable genetic findings for kidney patients.Design, setting, participants, & measurementsWe developed a return of results workflow in collaborations with clinicians for the retrospective recontact of adult nephrology patients who had been recruited into a biobank research study for exome sequencing and were

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Lee, Stuart, Michael Lawrence, and Michael I. Love. "Fluent genomics with plyranges and tximeta." F1000Research 9 (February 12, 2020): 109. http://dx.doi.org/10.12688/f1000research.22259.1.

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We construct a simple workflow for fluent genomics data analysis using the R/Bioconductor ecosystem. This involves three core steps: import the data into an appropriate abstraction, model the data with respect to the biological questions of interest, and integrate the results with respect to their underlying genomic coordinates. Here we show how to implement these steps to integrate published RNA-seq and ATAC-seq experiments on macrophage cell lines. Using tximeta, we import RNA-seq transcript quantifications into an analysis-ready data structure, called the SummarizedExperiment, that contains

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Xiao, Nan, Soner Koc, David Roberson, Phillip Brooks, Manisha Ray, and Dennis Dean. "BCO App: tools for generating BioCompute Objects from next-generation sequencing workflows and computations." F1000Research 9 (September 16, 2020): 1144. http://dx.doi.org/10.12688/f1000research.25902.1.

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The BioCompute Object (BCO) standard is an IEEE standard (IEEE 2791-2020) designed to facilitate the communication of next-generation sequencing data analysis with applications across academia, government agencies, and industry. For example, the Food and Drug Administration (FDA) supports the standard for regulatory submissions and includes the standard in their Data Standards Catalog for the submission of HTS data. We created the BCO App to facilitate BCO generation in a range of computational environments and, in part, to participate in the Advanced Track of the precisionFDA BioCompute Objec

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Pavlovikj, Natasha, Joao Carlos Gomes-Neto, Jitender S. Deogun, and Andrew K. Benson. "ProkEvo: an automated, reproducible, and scalable framework for high-throughput bacterial population genomics analyses." PeerJ 9 (May 21, 2021): e11376. http://dx.doi.org/10.7717/peerj.11376.

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Whole Genome Sequence (WGS) data from bacterial species is used for a variety of applications ranging from basic microbiological research, diagnostics, and epidemiological surveillance. The availability of WGS data from hundreds of thousands of individual isolates of individual microbial species poses a tremendous opportunity for discovery and hypothesis-generating research into ecology and evolution of these microorganisms. Flexibility, scalability, and user-friendliness of existing pipelines for population-scale inquiry, however, limit applications of systematic, population-scale approaches.

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Aryan, Zahra, Attila Szanto, Angeliki Pantazi, et al. "Moving Genomics to Routine Care." Circulation: Genomic and Precision Medicine 13, no. 5 (2020): 406–16. http://dx.doi.org/10.1161/circgen.120.002961.

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Background: Whole-genome sequencing (WGS) costs are falling, yet, outside oncology, this information is seldom used in adult clinics. We piloted a rapid WGS (rWGS) workflow, focusing initially on estimating power for a feasibility study of introducing genome information into acute cardiovascular care. Methods: A prospective implementation study was conducted to test the feasibility and clinical utility of rWGS in acute cardiovascular care. rWGS was performed on 50 adult patients with acute cardiovascular events and cardiac arrest survivors, testing for primary and secondary disease-causing var

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Juve, Gideon, Ewa Deelman, Karan Vahi, and Gaurang Mehta. "Experiences with Resource Provisioning for Scientific Workflows Using Corral." Scientific Programming 18, no. 2 (2010): 77–92. http://dx.doi.org/10.1155/2010/208568.

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The development of grid and workflow technologies has enabled complex, loosely coupled scientific applications to be executed on distributed resources. Many of these applications consist of large numbers of short-duration tasks whose runtimes are heavily influenced by delays in the execution environment. Such applications often perform poorly on the grid because of the large scheduling overheads commonly found in grids. In this paper we present a provisioning system based on multi-level scheduling that improves workflow runtime by reducing scheduling overheads. The system reserves resources fo

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Feofanova, Elena Valeryevna, Guo-Qiang Zhang, Samden Lhatoo, Ginger A. Metcalf, Eric Boerwinkle, and Eric Venner. "The Implementation Science for Genomic Health Translation (INSIGHT) Study in Epilepsy: Protocol for a Learning Health Care System." JMIR Research Protocols 10, no. 3 (2021): e25576. http://dx.doi.org/10.2196/25576.

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Background Genomic medicine is poised to improve care for common complex diseases such as epilepsy, but additional clinical informatics and implementation science research is needed for it to become a part of the standard of care. Epilepsy is an exemplary complex neurological disorder for which DNA diagnostics have shown to be advantageous for patient care. Objective We designed the Implementation Science for Genomic Health Translation (INSIGHT) study to leverage the fact that both the clinic and testing laboratory control the development and customization of their respective electronic health

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Singh, Gurnoor, Arnold Kuzniar, Matthijs Brouwer, et al. "Linked Data Platform for Solanaceae Species." Applied Sciences 10, no. 19 (2020): 6813. http://dx.doi.org/10.3390/app10196813.

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Genetics research is increasingly focusing on mining fully sequenced genomes and their annotations to identify the causal genes associated with traits (phenotypes) of interest. However, a complex trait is typically associated with multiple quantitative trait loci (QTLs), each comprising many genes, that can positively or negatively affect the trait of interest. To help breeders in ranking candidate genes, we developed an analytical platform called pbg-ld that provides semantically integrated geno- and phenotypic data on Solanaceae species. This platform combines both unstructured data from sci

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Ferrero, Enrico. "Using regulatory genomics data to interpret the function of disease variants and prioritise genes from expression studies." F1000Research 7 (January 29, 2018): 121. http://dx.doi.org/10.12688/f1000research.13577.1.

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The identification of therapeutic targets is a critical step in the research and developement of new drugs, with several drug discovery programmes failing because of a weak linkage between target and disease. Genome-wide association studies and large-scale gene expression experiments are providing insights into the biology of several common and complex diseases, but the complexity of transcriptional regulation mechanisms often limit our understanding of how genetic variation can influence changes in gene expression. Several initiatives in the field of regulatory genomics are aiming to close th

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Ferrero, Enrico. "Using regulatory genomics data to interpret the function of disease variants and prioritise genes from expression studies." F1000Research 7 (February 23, 2018): 121. http://dx.doi.org/10.12688/f1000research.13577.2.

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The identification of therapeutic targets is a critical step in the research and developement of new drugs, with several drug discovery programmes failing because of a weak linkage between target and disease. Genome-wide association studies and large-scale gene expression experiments are providing insights into the biology of several common diseases, but the complexity of transcriptional regulation mechanisms often limits our understanding of how genetic variation can influence changes in gene expression. Several initiatives in the field of regulatory genomics are aiming to close this gap by s

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Varshney, Gaurav K., Blake Carrington, Wuhong Pei, et al. "A high-throughput functional genomics workflow based on CRISPR/Cas9-mediated targeted mutagenesis in zebrafish." Nature Protocols 11, no. 12 (2016): 2357–75. http://dx.doi.org/10.1038/nprot.2016.141.

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Mahadevan, Anita, and S. K. Shankar. "Biobanking for cancer research: Preservation of tissue integrity – Some technical considerations." Indian Journal of Neurosurgery 01, no. 02 (2012): 130–38. http://dx.doi.org/10.4103/2277-9167.102279.

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Abstract Biobanking and biomarker discovery have become an integral part of neuro-oncology research. Towards achieving this end, the essential requirement is optimizing methods of tissue preservation of human tissues removed at surgery for diagnostic purposes and banking them for subserving future research. Owing to recent advances in molecular diagnostic tools, this clinical material has become a precious source for proteomic and genomic studies. The advent of biotechnological tools such as microarray, proteomics, and genomics has made it essential to preserve not just morphology but also the

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Warwick-Dugdale, Joanna, Natalie Solonenko, Karen Moore, et al. "Long-read viral metagenomics captures abundant and microdiverse viral populations and their niche-defining genomic islands." PeerJ 7 (April 25, 2019): e6800. http://dx.doi.org/10.7717/peerj.6800.

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Marine viruses impact global biogeochemical cycles via their influence on host community structure and function, yet our understanding of viral ecology is constrained by limitations in host culturing and a lack of reference genomes and ‘universal’ gene markers to facilitate community surveys. Short-read viral metagenomic studies have provided clues to viral function and first estimates of global viral gene abundance and distribution, but their assemblies are confounded by populations with high levels of strain evenness and nucleotide diversity (microdiversity), limiting assembly of some of the

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Johnson, James E., Praveen Kumar, Caleb Easterly, et al. "Improve your Galaxy text life: The Query Tabular Tool." F1000Research 7 (October 5, 2018): 1604. http://dx.doi.org/10.12688/f1000research.16450.1.

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Galaxy provides an accessible platform where multi-step data analysis workflows integrating disparate software can be run, even by researchers with limited programming expertise. Applications of such sophisticated workflows are many, including those which integrate software from different ‘omic domains (e.g. genomics, proteomics, metabolomics). In these complex workflows, intermediate outputs are often generated as tabular text files, which must be transformed into customized formats which are compatible with the next software tools in the pipeline. Consequently, many text manipulation steps a

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Johnson, James E., Praveen Kumar, Caleb Easterly, et al. "Improve your Galaxy text life: The Query Tabular Tool." F1000Research 7 (January 9, 2019): 1604. http://dx.doi.org/10.12688/f1000research.16450.2.

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Galaxy provides an accessible platform where multi-step data analysis workflows integrating disparate software can be run, even by researchers with limited programming expertise. Applications of such sophisticated workflows are many, including those which integrate software from different ‘omic domains (e.g. genomics, proteomics, metabolomics). In these complex workflows, intermediate outputs are often generated as tabular text files, which must be transformed into customized formats which are compatible with the next software tools in the pipeline. Consequently, many text manipulation steps a

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Crisan, Anamaria, Geoffrey McKee, Tamara Munzner, and Jennifer L. Gardy. "Evidence-based design and evaluation of a whole genome sequencing clinical report for the reference microbiology laboratory." PeerJ 6 (January 10, 2018): e4218. http://dx.doi.org/10.7717/peerj.4218.

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Background Microbial genome sequencing is now being routinely used in many clinical and public health laboratories. Understanding how to report complex genomic test results to stakeholders who may have varying familiarity with genomics—including clinicians, laboratorians, epidemiologists, and researchers—is critical to the successful and sustainable implementation of this new technology; however, there are no evidence-based guidelines for designing such a report in the pathogen genomics domain. Here, we describe an iterative, human-centered approach to creating a report template for communicat

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Xiong, Weili, Melinda A. McFarland, Cary Pirone, and Christine H. Parker. "Selection of Tree Nut Allergen Peptide Markers: A Need for Improved Protein Sequence Databases." Journal of AOAC INTERNATIONAL 102, no. 5 (2019): 1263–70. http://dx.doi.org/10.1093/jaoac/102.5.1263.

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Abstract Background: To effectively safeguard the food-allergic population and support compliance with food-labeling regulations, the food industry and regulatory agencies require reliable methods for food allergen detection and quantification. MS-based detection of food allergens relies on the systematic identification of robust and selective target peptide markers. The selection of proteotypic peptide markers, however, relies on the availability of high-quality protein sequence information, a bottleneck for the analysis of many plant-based proteomes. Method: In this work, data were compiled

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Lier, Amelie, Roland Penzel, Christoph Heining, et al. "Validating Comprehensive Next-Generation Sequencing Results for Precision Oncology: The NCT/DKTK Molecularly Aided Stratification for Tumor Eradication Research Experience." JCO Precision Oncology, no. 2 (November 2018): 1–13. http://dx.doi.org/10.1200/po.18.00171.

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Purpose Rapidly evolving genomics technologies, in particular comprehensive next-generation sequencing (NGS), have led to exponential growth in the understanding of cancer biology, shifting oncology toward personalized treatment strategies. However, comprehensive NGS approaches, such as whole-exome sequencing, have limitations that are related to the technology itself as well as to the input source. Hence, clinical implementation of comprehensive NGS in a quality-controlled diagnostic workflow requires both the standardization of sequencing procedures and continuous validation of sequencing re

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Chow, Julie C., Paul E. Anderson, and Andrew M. Shedlock. "Sea Turtle Population Genomic Discovery: Global and Locus-Specific Signatures of Polymorphism, Selection, and Adaptive Potential." Genome Biology and Evolution 11, no. 10 (2019): 2797–806. http://dx.doi.org/10.1093/gbe/evz190.

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Abstract In the era of genomics, single-nucleotide polymorphisms (SNPs) have become a preferred molecular marker to study signatures of selection and population structure and to enable improved population monitoring and conservation of vulnerable populations. We apply a SNP calling pipeline to assess population differentiation, visualize linkage disequilibrium, and identify loci with sex-specific genotypes of 45 loggerhead sea turtles (Caretta caretta) sampled from the southeastern coast of the United States, including 42 individuals experimentally confirmed for gonadal sex. By performing refe

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Cagliari, Deise, Guy Smagghe, Moises Zotti, and Clauvis Nji Tizi Taning. "RNAi and CRISPR/Cas9 as Functional Genomics Tools in the Neotropical Stink Bug, Euschistus heros." Insects 11, no. 12 (2020): 838. http://dx.doi.org/10.3390/insects11120838.

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The Neotropical brown stink bug, Euschistus heros, is one of the most important stink bug pests in leguminous plants in South America. RNAi and CRISPR/Cas9 are important and useful tools in functional genomics, as well as in the future development of new integrated pest management strategies. Here, we explore the use of these technologies as complementing functional genomic tools in E. heros. Three genes, abnormal wing disc (awd), tyrosine hydroxylase (th) and yellow (yel), known to be involved in wing development (awd) and the melanin pathway (th and yel) in other insects, were chosen to be e

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Rioth, Matthew J., David Staggs, and Jeremy Warner. "Incorporation of externally generated next-generation tumor genotyping into clinical and research workflows: Successes and lessons learned." Journal of Clinical Oncology 32, no. 30_suppl (2014): 156. http://dx.doi.org/10.1200/jco.2014.32.30_suppl.156.

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156 Background: The future of oncology will increasingly utilize information about tumor genomics. A growing number of tumor subtypes require genomic information as standard of care to inform treatment decisions. Clinical decision support (CDS) systems are able to improve healthcare and ensure best practices, but rely on machine-readable data. Typically, 3rd party genotyping results are returned in PDF reports that are not computable for standard presentation, CDS, or research purposes. Proposed oncology CDS platforms (such as CancerLinQ) will require computable tumor genomic information. Meth

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Schäfer, Richard A., Steffen C. Lott, Jens Georg, Björn A. Grüning, Wolfgang R. Hess, and Björn Voß. "GLASSgo in Galaxy: high-throughput, reproducible and easy-to-integrate prediction of sRNA homologs." Bioinformatics 36, no. 15 (2020): 4357–59. http://dx.doi.org/10.1093/bioinformatics/btaa556.

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Abstract Motivation The correct prediction of bacterial sRNA homologs is a prerequisite for many downstream analyses based on comparative genomics, but it is frequently challenging due to the short length and distinct heterogeneity of such homologs. GLobal Automatic Small RNA Search go (GLASSgo) is an efficient tool for the prediction of sRNA homologs from a single input query. To make the algorithm available to a broader community, we offer a Docker container along with a free-access web service. For non-computer scientists, the web service provides a user-friendly interface. However, capabil

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Saito, Kenji, Soichi Arai, and Hisanori Kato. "A nutrigenomics database – integrated repository for publications and associated microarray data in nutrigenomics research." British Journal of Nutrition 94, no. 4 (2005): 493–95. http://dx.doi.org/10.1079/bjn20051536.

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In the current situation where microarray data in the field of nutritional genomics (nutrigenomics) are accumulating rapidly, there is imminent need for an efficient data infrastructure to support research workflow. We have established a web-based, integrated database of the publications and microarray expression data in the field of nutrigenomics. The registered data include links to external databases such as PubMed of the National Center for Biotechnology Information and public microarray databases that contain Minimum Information About a Microarray Experiment-compliant microarray expressio

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Du, Yuheng, Qianhui Huang, Cedric Arisdakessian, and Lana X. Garmire. "Evaluation of STAR and Kallisto on Single Cell RNA-Seq Data Alignment." G3: Genes|Genomes|Genetics 10, no. 5 (2020): 1775–83. http://dx.doi.org/10.1534/g3.120.401160.

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Alignment of scRNA-Seq data are the first and one of the most critical steps of the scRNA-Seq analysis workflow, and thus the choice of proper aligners is of paramount importance. Recently, STAR an alignment method and Kallisto a pseudoalignment method have both gained a vast amount of popularity in the single cell sequencing field. However, an unbiased third-party comparison of these two methods in scRNA-Seq is lacking. Here we conduct a systematic comparison of them on a variety of Drop-seq, Fluidigm and 10x genomics data, from the aspects of gene abundance, alignment accuracy, as well as co

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Yu, Liping, Silin Sa, and Alice Wang. "11 A multi-physics approach enabling rare cell isolation with high recovery and high purity." Journal for ImmunoTherapy of Cancer 8, Suppl 3 (2020): A11. http://dx.doi.org/10.1136/jitc-2020-sitc2020.0011.

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BackgroundAdvancements in fields of multi-omics analysis and cell-based therapies depend upon efficient cell processing tools to isolate rare cancer and immune cells from complex biologic samples as an initial step in sample preparation. Conventional technologies are limited in automation, recovery and purity. We present an integrated system based on multiple physics principles with built-in novel technologies to achieve cell purification, concentration and target cell isolation, with high recovery at an unprecedented flow rate. This platform, the Multi-physics Automated Reconfigurable Separat

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Warner, Jeremy L., Matthew J. Rioth, Kenneth D. Mandl, et al. "SMART precision cancer medicine: a FHIR-based app to provide genomic information at the point of care." Journal of the American Medical Informatics Association 23, no. 4 (2016): 701–10. http://dx.doi.org/10.1093/jamia/ocw015.

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Abstract Background Precision cancer medicine (PCM) will require ready access to genomic data within the clinical workflow and tools to assist clinical interpretation and enable decisions. Since most electronic health record (EHR) systems do not yet provide such functionality, we developed an EHR-agnostic, clinico-genomic mobile app to demonstrate several features that will be needed for point-of-care conversations. Methods Our prototype, called Substitutable Medical Applications and Reusable Technology (SMART)® PCM, visualizes genomic information in real time, comparing a patient’s diagnosis-

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