Deep Sequencing Data Analysis

Bibliographische Detailangaben
Körperschaft: SpringerLink (Online service)
Weitere Verfasser: Shomron, Noam (HerausgeberIn)
Zusammenfassung:X, 374 p. 92 illus., 81 illus. in color.
text
Sprache:Englisch
Veröffentlicht: New York, NY : Springer US : Imprint: Humana, 2021.
Ausgabe:2nd ed. 2021.
Schriftenreihe:Methods in Molecular Biology, 2243
Schlagworte:
Online-Zugang:https://doi.org/10.1007/978-1-0716-1103-6
Format: Elektronisch Buch
Inhaltsangabe:
  • 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 Analysisto 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. .