Sequenza: allele-specific copy number and mutation profiles from tumor sequencing data

Favero, Francesco; Joshi, Tejal; Marquard, Andrea Marion; Birkbak, Nicolai J.; Krzystanek, Marcin; Li, Qiyuan; Szállási, Zoltán; Eklund, Aron C.

doi:10.1093/annonc/mdu479

Cited by 667 publications

(658 citation statements)

References 24 publications

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“…The ratio R=X is the proportion of reads supporting the mutant allele, known as the VAF. For CNAs, Canopy directly takes output from FALCON (28), FALCON-X, or other allele-specific copy number estimation methods (29). These outputs are in the form of estimated major and minor copy number ratios, denoted by W M ∈ R T×N and W m ∈ R T×N , respectively, with their corresponding standard errors « M ∈ R T×N and « m ∈ R T×N .…”

Section: Resultsmentioning

confidence: 99%

“…The input to Canopy are VAFs of somatic SNAs along with allele-specific coverage ratios between the tumor and matched normal sample for somatic copy number calls. These quantities can be directly taken from the output of existing software (28)(29)(30)(31). Canopy provides a general mathematical framework for pooling data across samples and sites to infer the underlying phylogeny.…”

Section: Significancementioning

confidence: 99%

See 1 more Smart Citation

Assessing intratumor heterogeneity and tracking longitudinal and spatial clonal evolutionary history by next-generation sequencing

Jiang

Qiu

Minn

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

219

241

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Cancer is a disease driven by evolutionary selection on somatic genetic and epigenetic alterations. Here, we propose Canopy, a method for inferring the evolutionary phylogeny of a tumor using both somatic copy number alterations and single-nucleotide alterations from one or more samples derived from a single patient. Canopy is applied to bulk sequencing datasets of both longitudinal and spatial experimental designs and to a transplantable metastasis model derived from human cancer cell line MDA-MB-231. Canopy successfully identifies cell populations and infers phylogenies that are in concordance with existing knowledge and ground truth. Through simulations, we explore the effects of key parameters on deconvolution accuracy and compare against existing methods. Canopy is an open-source R package available at https://cran.r-project.org/web/packages/Canopy/.intratumor heterogeneity | cancer evolution | clonal deconvolution | cancer genomics | phylogeny inference

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Section: Resultsmentioning

confidence: 99%

Section: Significancementioning

confidence: 99%

Assessing intratumor heterogeneity and tracking longitudinal and spatial clonal evolutionary history by next-generation sequencing

Jiang

Qiu

Minn

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

219

241

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“…The ngCGH module and RankSegmentation statistical algorithm in NEXUS software v7.5 (Biodiscovery) were used to define CNAs of each sample (44). We inferred the LOH events using Sequenza (45). All of the identified CNAs and LOH events were manually curated in terms of depth ratio and B allele frequency.…”

Section: Methodsmentioning

confidence: 99%

Whole-exome sequencing identifies recurrent AKT1 mutations in sclerosing hemangioma of lung

Jung

Kim

Lee

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

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Pulmonary sclerosing hemangioma (PSH) is a benign tumor with two cell populations (epithelial and stromal cells), for which genomic profiles remain unknown. We conducted exome sequencing of 44 PSHs and identified recurrent somatic mutations of AKT1 (43.2%) and β-catenin (4.5%). We used a second subset of 24 PSHs to confirm the high frequency of AKT1 mutations (overall 31/68, 45.6%; p.E17K, 33.8%) and recurrent β-catenin mutations (overall 3 of 68, 4.4%). Of the PSHs without AKT1 mutations, two exhibited AKT1 copy gain. AKT1 mutations existed in both epithelial and stromal cells. In two separate PSHs from one patient, we observed two different AKT1 mutations, indicating they were not disseminated but independent arising tumors. Because the AKT1 mutations were not found to cooccur with β-catenin mutations (or any other known driver alterations) in any of the PSHs studied, we speculate that this may be the singlemost common driver alteration to develop PSHs. Our study revealed genomic differences between PSHs and lung adenocarcinomas, including a high rate of AKT1 mutation in PSHs. These genomic features of PSH identified in the present study provide clues to understanding the biology of PSH and for differential genomic diagnosis of lung tumors.pulmonary sclerosing hemangioma | whole-exome sequencing | AKT1 mutation | copy number alteration

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“…Somatic variants called by Strelka (Saunders et al 2012) or VarDict (Lai et al 2016) have been used to create GEMINI (Paila et al 2013) databases and imported into Seave for short variant analysis. Likewise, copy number variants from Sequenza (Favero et al 2014), ClinSV (Minoche et al, in preparation) (genomes) or CNVkit (Talevich et al 2016) (panels) and structural variants from Manta (Chen et al 2016) can be imported into Seave's GBS to enable CNV and fusions analysis.…”

Section: Somatic Analysesmentioning

confidence: 99%

“…http://dx.doi.org/10.1101/258061 doi: bioRxiv preprint first posted online Jan. 31, 2018; (Saunders et al 2012) and VarDict (Lai et al 2016). Popular CNV and SV formats are also supported, including VCF and tabular formats from Sequenza (Favero et al 2014), CNVkit (Talevich et al 2016), LUMPY (Layer et al 2014), CNVnator (Abyzov et al 2011), Manta (Chen et al 2016) and ClinSV (Minoche et al, manuscript in preparation).…”

mentioning

confidence: 99%

Seave: a comprehensive web platform for storing and interrogating human genomic variation

Gayevskiy

Roscioli

Dinger

et al. 2018

Preprint

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Capability for genome sequencing and variant calling has increased dramatically, enabling large scale genomic interrogation of human disease. However, discovery is hindered by the current limitations in genomic interpretation, which remains a complicated and disjointed process. We introduce Seave, a web platform that enables variants to be easily filtered and annotated with in silico pathogenicity prediction scores and annotations from popular disease databases. Seave stores genomic variation of all types and sizes, and allows filtering for specific inheritance patterns, quality values, allele frequencies and gene lists. Seave is open source and deployable locally, or on a cloud computing provider, and works readily with gene panel, exome and whole genome data, scaling from single labs to multi-institution scale.

show abstract

Sequenza: allele-specific copy number and mutation profiles from tumor sequencing data

Abstract: We describe our algorithm and software for determining copy number profiles from tumor genome sequencing data, and find that it compares favorably to existing algorithms for the same purpose.

Cited by 667 publications

References 24 publications

Assessing intratumor heterogeneity and tracking longitudinal and spatial clonal evolutionary history by next-generation sequencing

Assessing intratumor heterogeneity and tracking longitudinal and spatial clonal evolutionary history by next-generation sequencing

Whole-exome sequencing identifies recurrent AKT1 mutations in sclerosing hemangioma of lung

Seave: a comprehensive web platform for storing and interrogating human genomic variation

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