Sequencing

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11th Annual <strong>Sequencing</strong>, Finishing, and Analysis in the Future Meeting A POWERFUL METHOD FOR COMPREHENSIVE STRUCTURAL VARIATION DETECTION WITH SHORT READS Wednesday, 1st June 16:35 La Fonda Ballroom Tech Talk (TT‐2.04) Nicholas Putnam 1 , Sanjeev Balakrishnan 1 , Jonathan Stites 1 , Richard E. Green 1,2 1 Dovetail Genomics, LLC, 2 University of California‐Santa Cruz Characterization and understanding of large genomic structural variants (SVs) is of fundamental importance for human health. Such variation is common, accounts for a large portion of all genomic variation in humans, and has been implicated in a diverse array of genomic diseases including cancers and psychiatric disorders. Despite its relevance to human health, cost‐effective methods for thorough characterization of SVs in human populations and individuals have remained elusive. Using in vitro proximity ligation, Dovetail Genomics has developed novel sequencing library preparation and analysis methods that bring significant power to bear on this problem. Applying these methods to a variety of samples, we have successfully detected and characterized both simple and complex structural variants across a wide range of size scales, including rearrangements flanked by tens of kilobases of low complexity sequence. Our method is rapid and affordable, enabling more effective research studies and the characterization of individual clinical cases. 121
11th Annual <strong>Sequencing</strong>, Finishing, and Analysis in the Future Meeting ANALYSIS OF THE FUNCTIONAL CONTENTS OF MICROBIAL COMMUNITIES USING A NOVEL QIAGEN BIOINFORMATICS PIPELINE Thursday, 2nd June 16:50 La Fonda Ballroom Tech Talk (TT‐2.05) Andreas Sand Pedersen, Francesco Strino, Aske Simon Christensen, Martin Bundgaard Qiagen Bioinformatics The field of microbial ecology is currently being revolutionized through next generation sequencing studies, revealing unprecedented detailed insight into environmental as well as host‐associated microbiomes. But still, very few tools offer efficient and user‐friendly analysis of the functional genomic contents of microbiomes. We have implemented a unique pipeline of tools for functional and comparative analysis of microbiomes as a component in QIAGEN Bioinformatics’ comprehensive solution for microbial genomics ‐ CLC Microbial Genomics Module. First step in this pipeline produces high‐quality metagenome contigs using a novel fast and highly memory efficient metagenome de novo assembler. The resulting contigs are subsequently CDS‐annotated using the MetaGeneMark plugin for CLC Genomics Workbench, and CDSs are annotated with PFAM protein families, GO terms and/or top BLAST hits (using e.g. UniProt). Finally, the relative abundance of each identified functional genomic element is computed and presented to the user in a user‐friendly manner. The functional contents of individual samples can be studied in a tabular format or visualized as pie charts, while visual comparison of multiple samples is done using stacked bar charts, layered area charts and principal coordinate plots. Finally, statistical comparison of multiple microbiome samples can be done to back‐up our observations. All visualisations and statistical analysis can be performed in the context of user‐defined meta‐information such as patient/control data. We will present benchmarks of this pipeline, performed on both previously published mock community datasets and several recently published simulated microbiome datasets, designed for benchmarking of microbiome analysis solutions. We demonstrate that QIAGEN Bioinformatics’ new metagenome de novo assembler runs as fast as the fastest alternative (MegaHit) but uses only a fraction of the memory required by any other benchmarked de novo assembler. At the same time it produces contigs that are both longer than the contigs produced by other popular metagenome assemblers (e.g. MegaHit and IDBA_UD) and are of significantly higher quality than the contigs produced by any other benchmarked de novo assembler. We furthermore demonstrate that the high‐quality contigs produced by our metagenome de novo assembler enables taxonomic and functional profiling of very high quality. And finally, we show that the complete analysis pipeline producing functional profiles from raw microbiome read datasets in five easy steps is able to reliably detect changes in the functional content of microbiomes with statistical significance. 122
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Sequencing

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