This volume offers detailed step-by-step instructions to allow beginners and experts alike to run appropriate copy number variants (CNV) detection software on a dataset of choice and discern between false positive noise and true positive CNV signals. Chapters guide readers through single nucleotide polymorphism (SNP) chips, optical mapping assembly techniques, and current open-source programs specializing in CNV detection. 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, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls.
Authoritative and cutting-edge,
Copy Number Variants: Methods and Protocols aims to provide guidance to Bioinformaticians and Molecular Biologists who are interested in identifying copy number variants (CNV) with a wide variety of experimental media
Reihe
Auflage
Sprache
Verlagsort
Zielgruppe
Illustrationen
25
11 s/w Abbildungen, 25 farbige Abbildungen
X, 206 p. 36 illus., 25 illus. in color.
Maße
Höhe: 260 mm
Breite: 183 mm
Dicke: 18 mm
Gewicht
ISBN-13
978-1-4939-8665-1 (9781493986651)
DOI
10.1007/978-1-4939-8666-8
Schweitzer Klassifikation
Identification of Copy Number Variants from SNP Arrays using PennCNV.- Using SAAS-CNV to Detect and Characterize Somatic Copy Number Alterations in Cancer Genomes from Next Generation Sequencing and SNP Array Data.- Statistical Detection of Genome Differences Based on CNV Segment.- Whole Genome Shotgun Sequence CNV Detection using Read Depth.- Read Depth Analysis to Identify CNV in Bacteria using CNOGpro.- Using HaMMLET for Bayesian Segmentation of WGS read-depth Data.- Split-Read InDel and Structural Variant Calling Using PINDEL.- Detecting Small Inversions using SRinversion.- Detection of CNVs in NGS data using VS-CNV.- Structural Variant Breakpoint Detection with novoBreak.- Use of RAPTR-SV to Identify SVs from Read Pairing and Split Read Signatures.- Versatile Identification of Copy Number Variants with Canvas.- Analysis of Population-genetic Properties of Copy Number Variations.- Validation of Genomic Structural Variants through Long Sequencing Technologies.- Structural Variation Detection and Analysis using Bionano Optical Mapping.
