Advances in sequencing technology have allowed scientists to study the human genome in greater depth and on a larger scale than ever before. 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, who seek 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.
|2||NGS file formats|
|3||Related algorithms and data structures|
|4||NGS read mapping|
|6||Single nucleotide variation (SNV) calling|
|7||Structural variation calling|
|9||Peak calling methods|
|10||Data compression techniques used in NGS files|
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