Advances in sequencing technology have allowed scientists to study the human genome in greater depth and on a larger scale than ever before – as many as hundreds of millions of short reads in the course of a few days. But what are the best ways to deal with this flood of data?
Algorithms for Next-Generation Sequencing
is an invaluable tool for students and researchers in bioinformatics and computational biology, biologists seeking to process and manage the data generated by next-generation sequencing, and as a textbook or a self-study resource. In addition to offering an in-depth description of the algorithms for processing sequencing data, it also presents useful case studies describing the applications of this technology.
Table of Contents
Chapter 1: Introduction
Chapter 2: Ngs File Formats
Chapter 3: Related Algorithms And Data Structures
Chapter 4: Ngs Read Mapping
Chapter 5: Genome Assembly
Chapter 6: Single Nucleotide Variation (Snv) Calling
Chapter 7: Structural Variation Calling
Chapter 8: Rna-Seq
Chapter 9: Peak Calling Methods
Chapter 10: Data Compression Techniques Used In Ngs Filles