By Ana M. Aransay, José Luis Lavín Trueba
ISBN-10: 3319313487
ISBN-13: 9783319313481
ISBN-10: 3319313509
ISBN-13: 9783319313504
High throughput sequencing (HTS) applied sciences have conquered the genomics and epigenomics worlds. The purposes of HTS equipment are extensive, and will be used to series every little thing from complete or partial genomes, transcriptomes, non-coding RNAs, ribosome profiling, to single-cell sequencing. Having such range of possible choices, there's a call for for info via study scientists with no event in HTS that have to select the main compatible technique or blend of systems and to outline their experimental designs to accomplish their particular ambitions. Field guidance for Genetic Experimental Designs in High-Throughput Sequencing goals to gather in one quantity all features that are meant to be taken into consideration whilst HTS applied sciences are being integrated right into a examine undertaking and the explanations in the back of them. furthermore, examples of a number of winning suggestions could be analyzed to make the purpose of the the most important gains. This publication should be of use to all scientist which are unexpected with HTS and wish to include such applied sciences to their research.
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Extra resources for Field Guidelines for Genetic Experimental Designs in High-Throughput Sequencing
Sample text
To generate high-quality assemblies from NGS data, one more or less follows the general workflow depicted in Fig. 5. , FASTQC) and plot k-mer frequencies to estimate genome size and complexity. Then, the overlap graph (as discussed above the more efficiently computed by de Bruijn graph) is created. To generate unitigs using a de Bruijn graph, k-mers of different lengths should be tested. K-mers that are too short will result in an assembly broken by short tandem repeats, while k-mers that are too long will result in assemblies broken at regions of low coverage.
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In some cases, additional sequencing can save a project; however, depending on the strategy, it may have been a waste. During the Project • Revise and optimize as you go. If a strategy is not working, try to diagnose the problem and fix it as early as possible. • Coordinate the work of the different teams involved, avoid redundant analysis, and establish clear dependencies and workflows. • Freeze assembly and annotation at the time downstream analyses and start to avoid multiple recomputations due to constant minor updates.
Field Guidelines for Genetic Experimental Designs in High-Throughput Sequencing by Ana M. Aransay, José Luis Lavín Trueba
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