ABSTRACT

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.

chapter 1|19 pages

Introduction

chapter 2|14 pages

NGS file formats

chapter 3|33 pages

Related algorithms and data structures

chapter 4|53 pages

NGS read mapping

chapter 5|51 pages

Genome assembly

chapter 6|33 pages

Single nucleotide variation (SNV) calling

chapter 7|36 pages

Structural variation calling

chapter 8|25 pages

RNA-seq

chapter 9|18 pages

Peak calling methods