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CopyVAE: a variatio...
CopyVAE: a variational autoencoder-based approach for copy number variation inference using single-cell transcriptomics
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- Kurt, Semih (författare)
- KTH,Beräkningsvetenskap och beräkningsteknik (CST),Science for Life Laboratory, SciLifeLab
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- Chen, Mandi (författare)
- KTH,Beräkningsvetenskap och beräkningsteknik (CST),Science for Life Laboratory, SciLifeLab
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- Toosi, Hosein (författare)
- KTH,Beräkningsvetenskap och beräkningsteknik (CST),Science for Life Laboratory, SciLifeLab
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- Chen, Xinsong (författare)
- Karolinska Institutet,Department of Oncology and Pathology, Karolinska Institutet, Solna, 171 77, Sweden
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- Engblom, Camilla (författare)
- Karolinska Institutet,Department of Cell and Molecular Biology, Karolinska Institutet, Solna, 171 77, Sweden
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- Mold, Jeff (författare)
- Department of Cell and Molecular Biology, Karolinska Institutet, Solna, 171 77, Sweden
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- Hartman, Johan (författare)
- Department of Oncology and Pathology, Karolinska Institutet, Solna, 171 77, Sweden; Department of Clinical Pathology and Cytology, Karolinska University Laboratory, Solna, 171 76, Sweden
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- Lagergren, Jens (författare)
- KTH,Beräkningsvetenskap och beräkningsteknik (CST),Science for Life Laboratory, SciLifeLab
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(creator_code:org_t)
- Oxford University Press, 2024
- 2024
- Engelska.
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Ingår i: Bioinformatics. - : Oxford University Press. - 1367-4803 .- 1367-4811. ; 40:5
- Relaterad länk:
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https://doi.org/10.1...
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https://urn.kb.se/re...
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https://doi.org/10.1...
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http://kipublication...
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Abstract
Ämnesord
Stäng
- Motivation: Copy number variations (CNVs) are common genetic alterations in tumour cells. The delineation of CNVs holds promise for enhancing our comprehension of cancer progression. Moreover, accurate inference of CNVs from single-cell sequencing data is essential for unravelling intratumoral heterogeneity. However, existing inference methods face limitations in resolution and sensitivity. Results: To address these challenges, we present CopyVAE, a deep learning framework based on a variational autoencoder architecture. Through experiments, we demonstrated that CopyVAE can accurately and reliably detect CNVs from data obtained using single-cell RNA sequencing. CopyVAE surpasses existing methods in terms of sensitivity and specificity. We also discussed CopyVAE’s potential to advance our understanding of genetic alterations and their impact on disease advancement. Availability and implementation: CopyVAE is implemented and freely available under MIT license at https://github.com/kurtsemih/copyVAE.
Ämnesord
- NATURVETENSKAP -- Biologi (hsv//swe)
- NATURAL SCIENCES -- Biological Sciences (hsv//eng)
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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