Biological Sequence Analysis Using the SeqAn C++ Library
Purchasing Options
Features
- Offers a collection of functional, well-designed algorithmic components
- Illustrates the advantage of using a software library
- Covers the design principles and programming techniques of SeqAn
- Presents the components supplied by SeqAn, such as sequence data structures, pattern and motif searching, string indices, and graphs
- Shows how SeqAn can be used to solve biological sequence problems, including genome alignment, consensus sequence computation, and the construction of a suffix array algorithm
Summary
An Easy-to-Use Research Tool for Algorithm Testing and Development
Before the SeqAn project, there was clearly a lack of available implementations in sequence analysis, even for standard tasks. Implementations of needed algorithmic components were either unavailable or hard to access in third-party monolithic software products. Addressing these concerns, the developers of SeqAn created a comprehensive, easy-to-use, open source C++ library of efficient algorithms and data structures for the analysis of biological sequences. Written by the founders of this project, Biological Sequence Analysis Using the SeqAn C++ Library covers the SeqAn library, its documentation, and the supporting infrastructure.
The first part of the book describes the general library design. It introduces biological sequence analysis problems, discusses the benefit of using software libraries, summarizes the design principles and goals of SeqAn, details the main programming techniques used in SeqAn, and demonstrates the application of these techniques in various examples. Focusing on the components provided by SeqAn, the second part explores basic functionality, sequence data structures, alignments, pattern and motif searching, string indices, and graphs. The last part illustrates applications of SeqAn to genome alignment, consensus sequence in assembly projects, suffix array construction, and more.
This handy book describes a user-friendly library of efficient data types and algorithms for sequence analysis in computational biology. SeqAn enables not only the implementation of new algorithms, but also the sound analysis and comparison of existing algorithms.
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Table of Contents
THE SEQAN PROJECT
Background
Sequences in Bioinformatics
Sequence Analysis
Software Libraries
SeqAn
Design of SeqAn
Contents of SeqAn
Testing
Documentation
Distribution
Library Design
Design Overview
Design Goals
Programming Techniques
The C++ Programming Language
Generic Programming
Template Subclassing
Global Function Interfaces
Metafunctions
Further Techniques
The Design in Examples
Example 1: Value Counting
Example 2: Locality-Sensitive Hashing
LIBRARY CONTENTS
Basics
Containers and Values
Memory Allocation
Move Operations
Alphabets
Iterators
Conversions
Sequences
Strings
Overflow Strategies
String Specializations
Sequence Adaptors
Iterating Sequences
Sequence Modifiers
Segments
Comparators
String Sets
Sequence Conversion
File Input/Output
Alignments
Gaps Data Structures
Alignment Data Structures
Alignment Scoring
Alignment Problems Overview
Global Alignments
Chaining
Pattern Matching
Exact Searching
Exact Searching of Multiple Needles
Approximate Searching
Other Pattern Matching Problems
Motif Finding
Local Alignments
Seed-Based Motif Search
Multiple Sequence Motifs
Indices
Working with Indices
q-Gram Indices
Suffix Arrays
Enhanced Suffix Arrays
Graphs
Automata
Alignment Graphs
APPLICATIONS
Aligning Sequences with LAGAN
The LAGAN Algorithm
Implementation of LAGAN
Results
Multiple Alignment with Segments
The Algorithm
Implementation
Results
Basic Statistical Indices for SeqAn
Statistical Indices and Biological Sequence Analysis
Mathematical Outline
SeqAn Algorithms and Data Types
Implementation Outline
A BWT-Based Suffix Array Construction
Introduction to BWTWalk
The Main Idea of BWTWalk
Saving Space
SeqAn Implementation of BWTWalkFast
Containers with and without Fast Random Access
In-Place Version
Experiments
Conclusion
Bibliography
Index
