Command Line Tools for Genomic Data Science

Start Date: 11/05/2018

Course Type: Common Course

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Introduces to the commands that you need to manage and analyze directories, files, and large sets of genomic data. This is the fourth course in the Genomic Big Data Science Specialization from Johns Hopkins University.

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Introduces to the commands that you need to manage and analyze directories, files, and large sets of

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Compression of Genomic Re-Sequencing Data High-throughput sequencing technologies have led to a dramatic decline of genome sequencing costs and to an astonishingly rapid accumulation of genomic data. These technologies are enabling ambitious genome sequencing endeavours, such as the 1000 Genomes Project and 1001 ("Arabidopsis thaliana") Genomes Project. The storage and transfer of the tremendous amount of genomic data have become a mainstream problem, motivating the development of high-performance compression tools designed specifically for genomic data. A recent surge of interest in the development of novel algorithms and tools for storing and managing genomic re-sequencing data emphasizes the growing demand for efficient methods for genomic data compression.
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Compression of Genomic Re-Sequencing Data The compression ratio of currently available genomic data compression tools ranges between 65-fold and 1,200-fold for human genomes. Very close variants or revisions of the same genome can be compressed very efficiently (for example, 18,133 compression ratio was reported for two revisions of the same A. thaliana genome, which are 99.999% identical). However, such compression is not indicative of the typical compression ratio for different genomes (individuals) of the same organism. The most common encoding scheme amongst these tools is Huffman coding, which is used for lossless data compression.
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