Large-scale Genome Sequence Processing - Masahiro Kasahara

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Large-scale Genome Sequence Processing

By: Masahiro Kasahara, Shinichi Morishita

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Hardcover | 7 July 2006

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248 Pages

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24.13 x 15.88 x 1.91

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Efficient computer programs have made it possible to elucidate and analyze large-scale genomic sequences. Fundamental tasks, such as the assembly of numerous whole-genome shotgun fragments, the alignment of complementary DNA sequences with a long genome, and the design of gene-specific primers or oligomers, require efficient algorithms and state-of-the-art implementation techniques. This textbook emphasizes basic software implementation techniques for processing large-scale genome sequences and provides executable sample programs.

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Preface	p. vii
Simple String Search	p. 1
Storing a String in an Array	p. 1
Brute-Force String Search	p. 2
Encoding Strings into Integers	p. 4
Sorting k-mer Integers and a Binary Search	p. 7
Binary Search for the Boundaries of Blocks	p. 8
Sorting	p. 11
Insertion Sort	p. 11
Merge Sort	p. 12
Worst-Case Time Complexity of Algorithms	p. 16
Heap Sort	p. 17
Randomized Quick Sort	p. 22
Improving the Performance of Quick Sort	p. 27
Ternary Split Quick Sort	p. 32
Radix Sort	p. 33
Lookup Tables	p. 39
Direct-Address Tables	p. 39
Hash Tables	p. 41
Table Size	p. 44
Using the Frequencies of k-mers	p. 45
Techniques for Reducing Table Size	p. 46
Suffix Arrays	p. 51
Suffix Trees	p. 52
Suffix Arrays	p. 54
Binary Search of Suffix Arrays for Queries	p. 56
Using the Longest Common Prefix Information to Accelerate the Search	p. 58
Computing the Longest Common Prefixes	p. 62
Application to Occurrence Frequencies of k-mers	p. 65
Application to the Longest Common Factors	p. 67
Suffix Array Construction - Doubling	p. 68
Larsson-Sadakane Algorithm	p. 69
Linear-Time Suffix Array Construction	p. 74
A Note on Practical Performance	p. 81
Space-Efficient String Search	p. 83
Rabin-Karp Algorithm	p. 83
Accelerating the Brute-Force String Search	p. 86
Knuth-Morris-Pratt Algorithm	p. 88
Bad Character Heuristics	p. 94
Approximate String Search	p. 99
Edit Operations and Alignments	p. 101
Edit Graphs and Dynamic Programming	p. 103
Needleman-Wunsch Algorithm	p. 105
Smith-Waterman Algorithm for Computing Local Alignments	p. 108
Overlap Alignments	p. 111
Alignment of cDNA Sequences with Genomes and Affine Gap Penalties	p. 114
Gotoh's Algorithm for Affine Gap Penalties	p. 116
Hirschberg's Space Reduction Technique	p. 120
Seeded Alignments	p. 125
Sensitivity and Specificity	p. 126
Computing Sensitivity and Specificity	p. 129
Multiple Hits of Seeds	p. 131
Gapped Seeds	p. 134
Chaining and Comparative Genomics	p. 135
Design of Highly Specific Oligomers	p. 141
Seeds for Computing Mismatch Tolerance	p. 145
Naive Algorithm	p. 145
BYP Method	p. 146
Partially Matching Seeds	p. 147
Overlapping, Partially Matching Seeds	p. 151
Whole Genome Shotgun Sequencing	p. 155
Sanger Method	p. 156
Improvements to the Sequencing Method	p. 159
Cloning Genomic DNA Fragments	p. 160
Basecalling	p. 163
Overview of Shotgun Sequencing	p. 165
Lander-Waterman Statistics	p. 170
Double-Stranded Assembly	p. 172
Overlap-Layout-Consensus	p. 175
Overlap	p. 175
Layout	p. 177
Consensus	p. 180
Practical Whole Genome Shotgun Assembly	p. 182
Vector Masking	p. 183
Quality Trimming	p. 186
Contamination Removal	p. 187
Overlap and Layout	p. 188
Seed and Extend	p. 188
Seeding	p. 190
Greedy Merging Approach	p. 191
Longer Repeat Sequence	p. 192
Iterative Improvements	p. 193
Accelerating Overlap Detection	p. 194
Repeat Sequence Detection	p. 196
Error Correction	p. 199
Repeat Separation	p. 199
Maximal Read Heuristics	p. 201
Paired Pair Heuristics	p. 202
Parallelization	p. 203
Eliminating Chimeric Reads	p. 204
Scaffolding	p. 205
How Many Mate Pairs Are Needed for Scaffolding?	p. 207
Iterative Improvements	p. 208
Consensus	p. 210
Quality Assessment	p. 211
Past and Future	p. 213
Software Availability	p. 221
Bibliography	p. 223
Index	p. 233
Table of Contents provided by Ingram. All Rights Reserved.

Large-scale Genome Sequence Processing

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