SCCNV: A Software Tool for Identifying Copy Number Variation From Single-Cell Whole-Genome Sequencing
Identification of de novo copy number variations (CNVs) across the genome in single cells requires single-cell whole-genome amplification (WGA) and sequencing. Although many experimental protocols of amplification methods have been developed, all suffer from uneven distribution of read depth across...
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Frontiers Media S.A.
2020-11-01
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| Series: | Frontiers in Genetics |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fgene.2020.505441/full |
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| author | Xiao Dong Lei Zhang Xiaoxiao Hao Tao Wang Jan Vijg Jan Vijg |
| author_facet | Xiao Dong Lei Zhang Xiaoxiao Hao Tao Wang Jan Vijg Jan Vijg |
| author_sort | Xiao Dong |
| collection | DOAJ |
| description | Identification of de novo copy number variations (CNVs) across the genome in single cells requires single-cell whole-genome amplification (WGA) and sequencing. Although many experimental protocols of amplification methods have been developed, all suffer from uneven distribution of read depth across the genome after sequencing of DNA amplicons, which constrains the usage of conventional CNV calling methodologies. Here, we present SCCNV, a software tool for detecting CNVs from whole genome-amplified single cells. SCCNV is a read-depth based approach with adjustment for the WGA bias. We demonstrate its performance by analyzing data obtained with most of the single-cell amplification methods that have been employed for CNV analysis, including DOP-PCR, MDA, MALBAC, and LIANTI. SCCNV is freely available at https://github.com/biosinodx/SCCNV. |
| first_indexed | 2024-12-23T04:37:09Z |
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| id | doaj.art-dbe66f68a0094bf3992a6957189895e5 |
| institution | Directory Open Access Journal |
| issn | 1664-8021 |
| language | English |
| last_indexed | 2024-12-23T04:37:09Z |
| publishDate | 2020-11-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Genetics |
| spelling | doaj.art-dbe66f68a0094bf3992a6957189895e52022-12-21T17:59:51ZengFrontiers Media S.A.Frontiers in Genetics1664-80212020-11-011110.3389/fgene.2020.505441505441SCCNV: A Software Tool for Identifying Copy Number Variation From Single-Cell Whole-Genome SequencingXiao Dong0Lei Zhang1Xiaoxiao Hao2Tao Wang3Jan Vijg4Jan Vijg5Department of Genetics, Albert Einstein College of Medicine, Bronx, NY, United StatesDepartment of Genetics, Albert Einstein College of Medicine, Bronx, NY, United StatesDepartment of Genetics, Albert Einstein College of Medicine, Bronx, NY, United StatesDepartment of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, United StatesDepartment of Genetics, Albert Einstein College of Medicine, Bronx, NY, United StatesCenter for Single-Cell Omics in Aging and Disease, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, ChinaIdentification of de novo copy number variations (CNVs) across the genome in single cells requires single-cell whole-genome amplification (WGA) and sequencing. Although many experimental protocols of amplification methods have been developed, all suffer from uneven distribution of read depth across the genome after sequencing of DNA amplicons, which constrains the usage of conventional CNV calling methodologies. Here, we present SCCNV, a software tool for detecting CNVs from whole genome-amplified single cells. SCCNV is a read-depth based approach with adjustment for the WGA bias. We demonstrate its performance by analyzing data obtained with most of the single-cell amplification methods that have been employed for CNV analysis, including DOP-PCR, MDA, MALBAC, and LIANTI. SCCNV is freely available at https://github.com/biosinodx/SCCNV.https://www.frontiersin.org/articles/10.3389/fgene.2020.505441/fullsingle-cell whole-genome sequencingsingle-cell whole-genome amplificationamplification biascopy number variationsoftware development |
| spellingShingle | Xiao Dong Lei Zhang Xiaoxiao Hao Tao Wang Jan Vijg Jan Vijg SCCNV: A Software Tool for Identifying Copy Number Variation From Single-Cell Whole-Genome Sequencing Frontiers in Genetics single-cell whole-genome sequencing single-cell whole-genome amplification amplification bias copy number variation software development |
| title | SCCNV: A Software Tool for Identifying Copy Number Variation From Single-Cell Whole-Genome Sequencing |
| title_full | SCCNV: A Software Tool for Identifying Copy Number Variation From Single-Cell Whole-Genome Sequencing |
| title_fullStr | SCCNV: A Software Tool for Identifying Copy Number Variation From Single-Cell Whole-Genome Sequencing |
| title_full_unstemmed | SCCNV: A Software Tool for Identifying Copy Number Variation From Single-Cell Whole-Genome Sequencing |
| title_short | SCCNV: A Software Tool for Identifying Copy Number Variation From Single-Cell Whole-Genome Sequencing |
| title_sort | sccnv a software tool for identifying copy number variation from single cell whole genome sequencing |
| topic | single-cell whole-genome sequencing single-cell whole-genome amplification amplification bias copy number variation software development |
| url | https://www.frontiersin.org/articles/10.3389/fgene.2020.505441/full |
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