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|a Field Guidelines for Genetic Experimental Designs in High-Throughput Sequencing
|h [electronic resource] /
|c edited by Ana M. Aransay, José Luis Lavín Trueba.
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|a 1st ed. 2016.
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|a Cham :
|b Springer International Publishing :
|b Imprint: Springer,
|c 2016.
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|a XI, 399 p. 72 illus., 42 illus. in color.
|b online resource.
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|a The High Throughput Sequencing technologies triple-W discussion: Why to use HTS, What is the optimal HTS method to use, Which data analysis workflow to follow -- Whole genome sequencing recommendations -- Counseling for targeted DNA region re-sequencing -- Transcriptome profiling strategies -- Differential mRNA Alternative Splicing -- microRNA discovery and expression analysis in animals -- Analysis of Long Non-coding RNAs in RNA-seq data -- Ribosome profiling -- Genome-wide analysis of DNA methylation patterns by high-throughput sequencing -- Characterization of DNA-protein interactions: Design and analysis of ChIP-seq experiments -- PAR-CLIP: A genomic technique to dissect RNA-protein interactions -- Metagenomic design and sequencing -- A hitchhiker's guide to Metatranscriptomics -- Eukaryotic Single-Cell mRNA Sequencing -- Eukaryotic Single-Cell DNA Sequencing -- Submitting data to a public repository, the final step of a successful HTS experiment.
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|a High throughput sequencing (HTS) technologies have conquered the genomics and epigenomics worlds. The applications of HTS methods are wide, and can be used to sequence everything from whole or partial genomes, transcriptomes, non-coding RNAs, ribosome profiling, to single-cell sequencing. Having such diversity of alternatives, there is a demand for information by research scientists without experience in HTS that need to choose the most suitable methodology or combination of platforms and to define their experimental designs to achieve their specific objectives. Field Guidelines for Genetic Experimental Designs in High-Throughput Sequencing aims to collect in a single volume all aspects that should be taken into account when HTS technologies are being incorporated into a research project and the reasons behind them. Moreover, examples of several successful strategies will be analyzed to make the point of the crucial features. This book will be of use to all scientist that are unfamiliar with HTS and want to incorporate such technologies to their research.
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|a Human genetics.
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|a Systems biology.
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|a Biostatistics.
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|a Human Genetics.
|0 https://scigraph.springernature.com/ontologies/product-market-codes/B12008
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|a Systems Biology.
|0 https://scigraph.springernature.com/ontologies/product-market-codes/L15010
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|a Biostatistics.
|0 https://scigraph.springernature.com/ontologies/product-market-codes/L15020
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| 700 |
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|a Aransay, Ana M.
|e editor.
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
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| 700 |
1 |
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|a Lavín Trueba, José Luis.
|e editor.
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
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| 710 |
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|a SpringerLink (Online service)
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| 773 |
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|t Springer Nature eBook
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| 776 |
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|i Printed edition:
|z 9783319313481
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| 776 |
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|i Printed edition:
|z 9783319313498
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|i Printed edition:
|z 9783319810188
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|u https://doi.org/10.1007/978-3-319-31350-4
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|a Biomedical and Life Sciences (R0) (SpringerNature-43708)
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