scholarly journals Prioritisation of Structural Variant Calls in Cancer Genomes

2016 ◽  
Author(s):  
Miika J Ahdesmäki ◽  
Brad Chapman ◽  
Pablo E Cingolani ◽  
Oliver Hofmann ◽  
Aleksandr Sidoruk ◽  
...  
Keyword(s):  
Dna Sequence ◽  
Gene Fusion ◽  
Sequence Data ◽  
High Impact ◽  
Structural Variants ◽  
Short Read ◽  
Structural Variant ◽  
Dna Sequence Data ◽  
Cancer Genomes ◽  
Fusion Detection

AbstractSensitivity 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. 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.

scholarly journals Prioritisation of structural variant calls in cancer genomes

PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e3166 ◽  
Author(s):  
Miika J. Ahdesmäki ◽  
Brad A. Chapman ◽  
Pablo Cingolani ◽  
Oliver Hofmann ◽  
Aleksandr Sidoruk ◽  
...  
Keyword(s):  
Dna Sequence ◽  
Gene Fusion ◽  
Sequence Data ◽  
High Impact ◽  
Structural Variants ◽  
Short Read ◽  
Structural Variant ◽  
Dna Sequence Data ◽  
Cancer Genomes ◽  
Fusion Detection

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.

scholarly journals Parliament2: Accurate structural variant calling at scale

GigaScience ◽  
2020 ◽  
Vol 9 (12) ◽  
Author(s):  
Samantha Zarate ◽  
Andrew Carroll ◽  
Medhat Mahmoud ◽  
Olga Krasheninina ◽  
Goo Jun ◽  
...  
Keyword(s):  
Dna Sequence ◽  
Sequence Data ◽  
Variant Calling ◽  
Ethnically Diverse ◽  
Current Standard ◽  
Short Read ◽  
Size Classes ◽  
Dna Sequence Data ◽  
1000 Genomes ◽  
Cost Efficient

Abstract Background Structural variants (SVs) are critical contributors to genetic diversity and genomic disease. To predict the phenotypic impact of SVs, there is a need for better estimates of both the occurrence and frequency of SVs, preferably from large, ethnically diverse cohorts. Thus, the current standard approach requires the use of short paired-end reads, which remain challenging to detect, especially at the scale of hundreds to thousands of samples. Findings We present Parliament2, a consensus SV framework that leverages multiple best-in-class methods to identify high-quality SVs from short-read DNA sequence data at scale. Parliament2 incorporates pre-installed SV callers that are optimized for efficient execution in parallel to reduce the overall runtime and costs. We demonstrate the accuracy of Parliament2 when applied to data from NovaSeq and HiSeq X platforms with the Genome in a Bottle (GIAB) SV call set across all size classes. The reported quality score per SV is calibrated across different SV types and size classes. Parliament2 has the highest F1 score (74.27%) measured across the independent gold standard from GIAB. We illustrate the compute performance by processing all 1000 Genomes samples (2,691 samples) in <1 day on GRCH38. Parliament2 improves the runtime performance of individual methods and is open source (https://github.com/slzarate/parliament2), and a Docker image, as well as a WDL implementation, is available. Conclusion Parliament2 provides both a highly accurate single-sample SV call set from short-read DNA sequence data and enables cost-efficient application over cloud or cluster environments, processing thousands of samples.

scholarly journals DNA sonification for public engagement in bioinformatics

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Heleen Plaisier ◽  
Thomas R. Meagher ◽  
Daniel Barker
Keyword(s):  
Dna Sequence ◽  
Public Engagement ◽  
Sequence Data ◽  
Sensory Perception ◽  
Data Representation ◽  
Sequence Information ◽  
Dna Sequence Data ◽  
Public Events ◽  
Dna Base ◽  
Alternative Means

Abstract Objective Visualisation methods, primarily color-coded representation of sequence data, have been a predominant means of representation of DNA data. Algorithmic conversion of DNA sequence data to sound—sonification—represents an alternative means of representation that uses a different range of human sensory perception. We propose that sonification has value for public engagement with DNA sequence information because it has potential to be entertaining as well as informative. We conduct preliminary work to explore the potential of DNA sequence sonification in public engagement with bioinformatics. We apply a simple sonification technique for DNA, in which each DNA base is represented by a specific note. Additionally, a beat may be added to indicate codon boundaries or for musical effect. We report a brief analysis from public engagement events we conducted that featured this method of sonification. Results We report on use of DNA sequence sonification at two public events. Sonification has potential in public engagement with bioinformatics, both as a means of data representation and as a means to attract audience to a drop-in stand. We also discuss further directions for research on integration of sonification into bioinformatics public engagement and education.

A new Liopeltis Fitzinger, 1843 (Squamata: Colubridae) from Pulau Tioman, Peninsular Malaysia

Zootaxa ◽  
2020 ◽  
Vol 4766 (3) ◽  
pp. 472-484
Author(s):  
HANNAH E. SOM ◽  
L. LEE GRISMER ◽  
PERRY L. JR. WOOD ◽  
EVAN S. H. QUAH ◽  
RAFE M. BROWN ◽  
...  
Keyword(s):  
Mitochondrial Dna ◽  
New Species ◽  
Dna Sequence ◽  
Rare Species ◽  
Sequence Data ◽  
Peninsular Malaysia ◽  
Tropical Asia ◽  
Dna Sequence Data ◽  
A New Species ◽  
Lines Of Evidence

Liopeltis is a genus of poorly known, infrequently sampled species of colubrid snakes in tropical Asia. We collected a specimen of Liopeltis from Pulau Tioman, Peninsular Malaysia, that superficially resembled L. philippina, a rare species that is endemic to the Palawan Pleistocene Aggregate Island Complex, western Philippines. We analyzed morphological and mitochondrial DNA sequence data from the Pulau Tioman specimen and found distinct differences to L. philippina and all other congeners. On the basis of these corroborated lines of evidence, the Pulau Tioman specimen is described as a new species, L. tiomanica sp. nov. The new species occurs in sympatry with L. tricolor on Pulau Tioman, and our description of L. tiomanica sp. nov. brings the number of endemic amphibians and reptiles on Pulau Tioman to 12. 

scholarly journals Self-organizing Clustering: Non-hierarchical Clustering for Large Scale DNA Sequence Data

2007 ◽  
Vol 3 ◽  
pp. 193-197 ◽  
Author(s):  
Kou Amano ◽  
Hiroaki Ichikawa ◽  
Hidemitsu Nakamura ◽  
Hisataka Numa ◽  
Kaoru Fukami-Kobayashi ◽  
...  
Keyword(s):  
Dna Sequence ◽  
Hierarchical Clustering ◽  
Large Scale ◽  
Sequence Data ◽  
Dna Sequence Data ◽  
Self Organizing
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