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Prioritisation of structural variant calls in cancer genomes

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ABSTRACT

Sensitivity of short read DNA-sequencing for gene fusion detection is improving, but is hampered by the significant amount of noise composed of uninteresting or false positive hits in the data. In this paper we describe a tiered prioritisation approach to extract high impact gene fusion events from existing structural variant calls. Using cell line and patient DNA sequence data we improve the annotation and interpretation of structural variant calls to best highlight likely cancer driving fusions. We also considerably improve on the automated visualisation of the high impact structural variants to highlight the effects of the variants on the resulting transcripts. The resulting framework greatly improves on readily detecting clinically actionable structural variants.

No MeSH data available.


Svviz output for the FGFR3-TACC3 fusion (tandem duplication) in the RT4 cell line.Read evidence is shown for both how the last intron of FGFR3 is fused to an exon of TACC3 as well as for the reference alleles.
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fig-3: Svviz output for the FGFR3-TACC3 fusion (tandem duplication) in the RT4 cell line.Read evidence is shown for both how the last intron of FGFR3 is fused to an exon of TACC3 as well as for the reference alleles.

Mentions: Visualisation of structural variants to highlight the breakpoints and affected exons in a putative fusion transcript is an area of active development with no one tool currently being the industry standard. We initially identified Svviz (Spies et al., 2015), one of the earlier tools, to examine the validated fusion variants highlighted by prioritisation. The FGFR3-TACC3 tandem duplication (RT4 cell line) is shown in Fig. 3; TACC3 is not captured by the panel used and therefore no reads in support of the reference allele for TACC3 are shown. Svviz reassembles the reads around the putative breakpoints in its analysis and requires an amount of manual intervention.


Prioritisation of structural variant calls in cancer genomes
Svviz output for the FGFR3-TACC3 fusion (tandem duplication) in the RT4 cell line.Read evidence is shown for both how the last intron of FGFR3 is fused to an exon of TACC3 as well as for the reference alleles.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5382922&req=5

fig-3: Svviz output for the FGFR3-TACC3 fusion (tandem duplication) in the RT4 cell line.Read evidence is shown for both how the last intron of FGFR3 is fused to an exon of TACC3 as well as for the reference alleles.
Mentions: Visualisation of structural variants to highlight the breakpoints and affected exons in a putative fusion transcript is an area of active development with no one tool currently being the industry standard. We initially identified Svviz (Spies et al., 2015), one of the earlier tools, to examine the validated fusion variants highlighted by prioritisation. The FGFR3-TACC3 tandem duplication (RT4 cell line) is shown in Fig. 3; TACC3 is not captured by the panel used and therefore no reads in support of the reference allele for TACC3 are shown. Svviz reassembles the reads around the putative breakpoints in its analysis and requires an amount of manual intervention.

View Article: PubMed Central - HTML - PubMed

ABSTRACT

Sensitivity of short read DNA-sequencing for gene fusion detection is improving, but is hampered by the significant amount of noise composed of uninteresting or false positive hits in the data. In this paper we describe a tiered prioritisation approach to extract high impact gene fusion events from existing structural variant calls. Using cell line and patient DNA sequence data we improve the annotation and interpretation of structural variant calls to best highlight likely cancer driving fusions. We also considerably improve on the automated visualisation of the high impact structural variants to highlight the effects of the variants on the resulting transcripts. The resulting framework greatly improves on readily detecting clinically actionable structural variants.

No MeSH data available.