Sequana Coverage: Detection and Characterization of Genomic Variations using Running Median and Mixture Models | Zendy

Dimitri Desvillechabrol | Zendy; Christiane Bouchier | Zendy; Sean Kennedy | Zendy; Thomas Cokelaer | Zendy

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Sequana Coverage: Detection and Characterization of Genomic Variations using Running Median and Mixture Models

Author(s) -

Dimitri Desvillechabrol,

Christiane Bouchier,

Sean Kennedy,

Thomas Cokelaer

Publication year - 2018

Publication title -

gigascience

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 2.947

H-Index - 54

ISSN - 2047-217X

DOI - 10.1093/gigascience/giy110

Subject(s) - statistic , genome , mixture model , copy number variation , computer science , computational biology , biology , genetics , data mining , statistics , mathematics , artificial intelligence , gene

In addition to mapping quality information, the Genome coverage contains valuable biological information such as the presence of repetitive regions, deleted genes, or copy number variations (CNVs). It is essential to take into consideration atypical regions, trends (e.g., origin of replication), or known and unknown biases that influence coverage. It is also important that reported events have robust statistics (e.g. z-score) associated with their detections as well as precise location.

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