iFUSE: integrated fusion gene explorer

Hiltemann, Saskia; McClellan, Elizabeth; Nijnatten, Jos van; Horsman, Sebastiaan; Palli, Ivo; Alves, Inês Teles; Hartjes, Thomas; Trapman, Jan; Spek, Peter J. van der; Jenster, Guido; Stubbs, Andrew

doi:10.1093/bioinformatics/btt252

Cited by 9 publications

(5 citation statements)

References 17 publications

(16 reference statements)

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“…The VarFilter may be used to select those variants which have a high confidence based on the underlying sequence reads as specified as VQHIGH, and the SNPDiff tool can then be used to determine concordance of the NGS results with those of an orthogonal SNV detection platform such as an Affymetrix or Illumina SNP array. The JunctionDiff and Junction2Events tools are used to select fusion events and candidate fusion genes based on quality of the discordant reads used to detect the structural variation event [9]. …”

Section: Resultsmentioning

confidence: 99%

CGtag: complete genomics toolkit and annotation in a cloud-based Galaxy

Hiltemann¹,

Mei²,

Hollander³

et al. 2014

GigaSci

105

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BackgroundComplete Genomics provides an open-source suite of command-line tools for the analysis of their CG-formatted mapped sequencing files. Determination of; for example, the functional impact of detected variants, requires annotation with various databases that often require command-line and/or programming experience; thus, limiting their use to the average research scientist. We have therefore implemented this CG toolkit, together with a number of annotation, visualisation and file manipulation tools in Galaxy called CGtag (Complete Genomics Toolkit and Annotation in a Cloud-based Galaxy).FindingsIn order to provide research scientists with web-based, simple and accurate analytical and visualisation applications for the selection of candidate mutations from Complete Genomics data, we have implemented the open-source Complete Genomics tool set, CGATools, in Galaxy. In addition we implemented some of the most popular command-line annotation and visualisation tools to allow research scientists to select candidate pathological mutations (SNV, and indels). Furthermore, we have developed a cloud-based public Galaxy instance to host the CGtag toolkit and other associated modules.ConclusionsCGtag provides a user-friendly interface to all research scientists wishing to select candidate variants from CG or other next-generation sequencing platforms’ data. By using a cloud-based infrastructure, we can also assure sufficient and on-demand computation and storage resources to handle the analysis tasks. The tools are freely available for use from an NBIC/CTMM-TraIT (The Netherlands Bioinformatics Center/Center for Translational Molecular Medicine) cloud-based Galaxy instance, or can be installed to a local (production) Galaxy via the NBIC Galaxy tool shed.

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Section: Resultsmentioning

confidence: 99%

CGtag: complete genomics toolkit and annotation in a cloud-based Galaxy

Hiltemann¹,

Mei²,

Hollander³

et al. 2014

GigaSci

105

View full text Add to dashboard Cite

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“…Structural variants were evaluated for gene fusions with iFuse. 23 Characterisation of the mutational signature was done by comparison of the trinucleotide context of each SNV to the established COSMIC signatures using the MutationalPatterns R package (v1.0). 24…”

Section: Methodsmentioning

confidence: 99%

Molecular heterogeneity and early metastatic clone selection in testicular germ cell cancer development

et al. 2019

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Background Testicular germ cell cancer (TGCC), being the most frequent malignancy in young Caucasian males, is initiated from an embryonic germ cell. This study determines intratumour heterogeneity to unravel tumour progression from initiation until metastasis. Methods In total, 42 purified samples of four treatment-resistant nonseminomatous (NS) TGCC were investigated, including the precursor germ cell neoplasia in situ (GCNIS) and metastatic specimens, using whole-genome and targeted sequencing. Their evolution was reconstructed. Results Intratumour molecular heterogeneity did not correspond to the supposed primary tumour histological evolution. Metastases after systemic treatment could be derived from cancer stem cells not identified in the primary cancer. GCNIS mostly lacked the molecular marks of the primary NS and comprised dominant clones that failed to progress. A BRCA-like mutational signature was observed without evidence for direct involvement of BRCA1 and BRCA2 genes. Conclusions Our data strongly support the hypothesis that NS is initiated by whole-genome duplication, followed by chromosome copy number alterations in the cancer stem cell population, and accumulation of low numbers of somatic mutations, even in therapy-resistant cases. These observations of heterogeneity at all stages of tumourigenesis should be considered when treating patients with GCNIS-only disease, or with clinically overt NS.

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“…Read alignment/coverage and gene annotations for fusion genes Loupe, iFUSE [53], targetSeqView [47], AGFusion [58], BreakPoint Surveyor [59], and MAVIS [57] Multi-way View --…”

Section: Yes Yesmentioning

confidence: 99%

Visualization tools for human structural variations identified by whole-genome sequencing

Yokoyama

Kasahara

2019

J Hum Genet

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Visualizing structural variations (SVs) is a critical step for finding associations between SVs and human traits or diseases. Given that there are many sequencing platforms used for SV identification and given that how best to visualize SVs together with other data, such as read alignments and annotations, depends on research goals, there are dozens of SV visualization tools designed for different research goals and sequencing platforms. Here, we provide a comprehensive survey of over 30 SV visualization tools to help users choose which tools to use. This review targets users who wish to visualize a set of SVs identified from the massively parallel sequencing reads of an individual human genome. We first categorize the ways in which SV visualization tools display SVs into ten major categories, which we denote as view modules. View modules allow readers to understand the features of each SV visualization tool quickly. Next, we introduce the features of individual SV visualization tools from several aspects, including whether SV views are integrated with annotations, whether long-read alignment is displayed, whether underlying data structures are graph-based, the type of SVs shown, whether auditing is possible, whether bird's eye view is available, sequencing platforms, and the number of samples. We hope that this review will serve as a guide for readers on the currently available SV visualization tools and lead to the development of new SV visualization tools in the near future.

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iFUSE: integrated fusion gene explorer

Cited by 9 publications

References 17 publications

CGtag: complete genomics toolkit and annotation in a cloud-based Galaxy

CGtag: complete genomics toolkit and annotation in a cloud-based Galaxy

Molecular heterogeneity and early metastatic clone selection in testicular germ cell cancer development

Visualization tools for human structural variations identified by whole-genome sequencing

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