Sequencing

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11th Annual <strong>Sequencing</strong>, Finishing, and Analysis in the Future Meeting NUCLEOTID.ES OBJECTIVE BENCHMARKING OF BIOINFORMATICS SOFTWARE Thursday, 2nd June 10:40 La Fonda Ballroom Talk (OS‐5.01) Michael Barton Joint Genome Institute As novel technologies emerge, fueled by scientific questions, the number bioinformatics tools continues to grow. When publishing new bioinformatics software, the tool is typically compared against others’ using test data. Naturally, researchers will select the results that portray their software in the best way, which can lead to a subjective comparison, sometimes even lacking reproducibility. Combining this with the current large numbers of software publications in bioinformatics it is difficult for researchers to objectively evaluate which software will work best in their analysis, since different tools are rarely tested on identical data and settings for running tools can be very custom. To address these challenges, we developed the nucleotid.es project, which places bioinformatics tools in software containers that allow them to be used on any platform, and reproducibly benchmarked against reference sequencing data. This allows software to be evaluated simultaneously and without requiring manual installation or setting of parameters. The tools benchmarked in nucleotid.es are submitted by the bioinformatics community or created from the existing literature. This effectively crowd‐sources software from anyone who wishes to participate. The latest bioinformatics research can thus constantly be evaluated against the current existing corpus and the result of this benchmarking then shared with the wider bioinformatics community as they are generated. This talk will present nucleotid.es and the results of running this analysis on a range of genome assemblers. 105
11th Annual <strong>Sequencing</strong>, Finishing, and Analysis in the Future Meeting AUTOMATION AND MANAGEMENT OF INFLUENZA NEXT-GENERATION SEQUENCING DATA ANALYSIS AND QUALITY CONTROL PROCEDURES Thursday, 2nd June 11:00 La Fonda Ballroom Talk (OS‐5.02) Thomas Stark 1 , Samuel Shepard 2 , Sujatha Seenu 2 , Elizabeth Neuhaus 2 , John Barnes 2 1 Battelle Memorial Institute, Atlanta, GA, 2 Influenza Division, Centers for Disease Control and Prevention, The CDC Influenza Division recently transitioned to using next generation sequencing technologies for molecular surveillance and now routinely sequences original clinical specimens as part of its operational pipeline. A customized Clarity LIMS workflow supports these operations and serves an important role within this pipeline, particularly because it has been extensively configured to streamline high throughput sequencing tasks. This overall workflow includes automated queueing of available specimens from a central metadata store as well as auto‐assignment of samples to a central library construction workflow. Experimental procedures are easily tracked and quality control metrics are readily produced for each phase of the overall process, which includes monitoring of inprogress instrumentation as well as review of post‐run analysis results. Genome assembly of the LIMS‐staged samples is automatically scheduled on grid computing infrastructure as soon as NGS runs complete. Downstream curation and aggregate quality control assessments are also triggered automatically within this framework, enabling access to interpretation‐ready data as early as one hour following the completion of a 96‐plex Illumina MiSeq run. Our custom‐configured Clarity LIMS pipeline furnishes e‐mail status alerts and provides summary reports on a per‐run basis, two features that serve to notify submitters of completion or failure status in real time. This overall system has become a critical component of Influenza Genomics Team operations by minimizing clerical technical errors within the laboratory, by maintaining consistent records of laboratory metadata associated with these experimental procedures, by improving the timeliness of the availability of processed data through the automation of analysis, and by providing computational scrutiny of multiplexed data. Finally, this LIMS configuration and data management regime has been replicated in a cloudcomputing environment in order to establish a network of procedurally identical Influenza Reference Center satellite sites, which serve to increase national surveillance capacity, reduce turn‐around times for the availability of genetic data, and establish readiness for pandemic preparedness. 106
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Reliable solutions for focused NGS
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Sequencing

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