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This volume covers the detection of structural variants (SVs), which require different strategies than the ones used for single nucleotide variants (SNVs). This book aims to provide readers with a combination of the latest "wet lab" methods and computational pipelines that target all SV classes. The chapters in this book cover topics such as detection of transposable elements (TEs) from short read data; long read sequencing used for multiple variable number tandem repeat analysis; genomic mosaicism in the nervous system; and optical genome mapping. In the Neuromethods series style, chapters include the kind of detail and key advice from the specialists needed to get successful results in your laboratory.

Cutting-edge and comprehensive, Genomic Structural Variants in Nervous System Disorders is a valuable resource for scientists and researchers interested in learning more about this important field.