Deep sequencing data analysis / edited by Noam Shomron.Material type: TextSeries: Methods in molecular biology (Clifton, N.J.) ; 2243. | Springer protocols (Series)Publisher: New York, NY : Humana Press, Edition: Second editionDescription: 1 online resource (x, 374 pages) : illustrations (some color)Content type: text Media type: computer Carrier type: online resourceISBN: 9781071611036; 1071611038Subject(s): Nucleotide sequence -- Laboratory manuals | Nucleotide sequence -- Data processing -- Laboratory manuals | High-Throughput Nucleotide Sequencing -- methods | Nucleotide sequence -- Data processing | Nucleotide sequence | Bioinformatics | GeneticsGenre/Form: Laboratory manuals. | Electronic books | Laboratory Manual. Additional physical formats: Printed edition: No title; Printed edition: No title; Printed edition: No titleDDC classification: 572.8/633 LOC classification: QP625.N89NLM classification: QU 25Online resources: Click here to access online
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This second edition provides new and updated chapters from expert researchers in the field detailing methods used to study the multi-facet deep sequencing data field. Chapters guide readers through techniques for processing RNA-seq data, microbiome analysis, deep learning methodologies, and various approaches for the identification of sequence variants. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and cutting-edge, Deep Sequencing Data Analysis: Methods and Protocols, Second Edition aims to ensure successful results in the further study of this vital field.
Detecting Causal Variants in Mendelian Disorders using Whole-Genome Sequencing -- Statistical Considerations on NGS Data for Inferring Copy Number Variations -- Applications of Community Detection Algorithms to Large Biological Datasets -- Processing and Analysis of RNA-seq data from Public Resources -- Improved Analysis of High-throughput Sequencing Data Using Small Universal k-mer Hitting Sets -- An Introduction to Whole-metagenome Shotgun Sequencing Studies -- Microbiome Analysis using 16S Amplicon Sequencing: From Samples to ASVs -- RNA-Seq in Non-model Organisms -- Deep Learning Applied on Next Generation Sequencing Data Analysis -- Interrogating the Accessible Chromatin Landscape of Eukaryote Genomes using ATAC-seq -- Genome-Wide Noninvasive Prenatal Diagnosis of SNPs and Indels -- Genome-wide Noninvasive Prenatal Diagnosis of De Novo Mutations -- Accurate Imputation of Untyped Variants from Deep Sequencing Data -- Multi-region Sequence Analysis to Predict Intratumor Heterogeneity and Clonal Evolution -- Overcoming Interpretability in Deep Learning Cancer Classification -- Single-cell Transcriptome Profiling -- Biological Perspectives of RNA-sequencing Experimental Design -- Analysis of microRNA Regulation in Single Cells -- DNA Data Collection and Analysis in the Forensic Arena.
Includes bibliographical references and index.
Online resource; title from PDF title page (SpringerLink, viewed April 5, 2021).