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PopIns: population-scale detection of novel sequence insertions
Author(s) -
Birte Kehr,
Páll Melsted,
Bjarni V. Halldórsson
Publication year - 2015
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btv273
Subject(s) - contig , reference genome , computer science , sequence assembly , precision and recall , population , source code , sequence (biology) , 1000 genomes project , reliability (semiconductor) , computational biology , structural variation , data mining , genome , genetics , biology , artificial intelligence , power (physics) , gene , genotype , single nucleotide polymorphism , programming language , gene expression , demography , physics , transcriptome , quantum mechanics , sociology
The detection of genomic structural variation (SV) has advanced tremendously in recent years due to progress in high-throughput sequencing technologies. Novel sequence insertions, insertions without similarity to a human reference genome, have received less attention than other types of SVs due to the computational challenges in their detection from short read sequencing data, which inherently involves de novo assembly. De novo assembly is not only computationally challenging, but also requires high-quality data. Although the reads from a single individual may not always meet this requirement, using reads from multiple individuals can increase power to detect novel insertions.

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