AnnotSV: an integrated tool for structural variations annotation

被引:256
作者
Geoffroy, Veronique [1 ]
Herenger, Yvan [2 ]
Kress, Arnaud [3 ]
Stoetzel, Corinne [1 ]
Piton, Amelie [4 ,5 ]
Dollfus, Helene [1 ,6 ]
Muller, Jean [1 ,4 ]
机构
[1] Univ Strasbourg, Lab Genet Med, INSERM, UMR S,IGMA,Fac Med FMTS,U1112, Strasbourg, France
[2] CHU Tours, Serv Genet Med, Tours, France
[3] Univ Strasbourg, ICUBE, CNRS, CSTB,FMTS,UMR 7357, Strasbourg, France
[4] Hop Univ Strasbourg, Labs Diagnost Genet, IGMA, Strasbourg, France
[5] Univ Strasbourg, INSERM, U964, CNRS,Inst Genet & Biol Mol & Cellulaire,UMR7104, F-67400 Illkirch Graffenstaden, France
[6] Hop Univ Strasbourg, Ctr Reference Affect Rares Genet Opthalmol CARGO, Filiere SENSGENE, F-67091 Strasbourg, France
关键词
GENOMIC VARIANTS; DATABASE; HUMANS;
D O I
10.1093/bioinformatics/bty304
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Structural Variations (SV) are a major source of variability in the human genome that shaped its actual structure during evolution. Moreover, many human diseases are caused by SV, highlighting the need to accurately detect those genomic events but also to annotate them and assist their biological interpretation. Therefore, we developed AnnotSV that compiles functionally, regulatory and clinically relevant information and aims at providing annotations useful to (i) interpret SV potential pathogenicity and (ii) filter out SV potential false positive. In particular, AnnotSV reports heterozygous and homozygous counts of single nucleotide variations (SNVs) and small insertions/deletions called within each SV for the analyzed patients, this genomic information being extremely useful to support or question the existence of an SV. We also report the computed allelic frequency relative to overlapping variants from DGV (MacDonald et al., 2014), that is especially powerful to filter out common SV. To delineate the strength of AnnotSV, we annotated the 4751 SV from one sample of the 1000 Genomes Project, integrating the sample information of four million of SNV/indel, in less than 60 s.
引用
收藏
页码:3572 / 3574
页数:3
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