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The performance of individual CNV detection software and state-of-the-art sequencing. All analyses were performed using the Python and R programming languages.

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Comparison of CNVnator and Pindel tools basedon next generation sequencing data

The data used by the programs were obtained from 12 individuals of the Domestic Swine (Sus scrofa domestica) breed Wielka Biała Polska. DNA was isolated from blood and sequenced using the Illumina platform. The main intention of the work is to compare algorithms for CNV detection such as Split-Read, Paired-End Mapping, Read-Depth, Assembly-Based or Combinatorial Approach, with particular emphasis on Split-Read and Read-Depth algorithms, which found their use in Pindel and CNVnator software.

The paper is based on the literature on algorithms to help identify CNVs, the performance of individual CNV detection software and state-of-the-art sequencing. All analyses were performed using the Python and R programming languages.

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The performance of individual CNV detection software and state-of-the-art sequencing. All analyses were performed using the Python and R programming languages.

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