Epi-Impute: Single-Cell RNA-seq Imputation via Integration with Single-Cell ATAC-seq
Single-cell RNA-seq data contains a lot of dropouts hampering downstream analyses due to the low number and inefficient capture of mRNAs in individual cells. Here, we present Epi-Impute, a computational method for dropout imputation by reconciling expression and epigenomic data. Epi-Impute leverages...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-03-01
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| Series: | International Journal of Molecular Sciences |
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| Online Access: | https://www.mdpi.com/1422-0067/24/7/6229 |
| _version_ | 1797607917044629504 |
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| author | Mikhail Raevskiy Vladislav Yanvarev Sascha Jung Antonio Del Sol Yulia A. Medvedeva |
| author_facet | Mikhail Raevskiy Vladislav Yanvarev Sascha Jung Antonio Del Sol Yulia A. Medvedeva |
| author_sort | Mikhail Raevskiy |
| collection | DOAJ |
| description | Single-cell RNA-seq data contains a lot of dropouts hampering downstream analyses due to the low number and inefficient capture of mRNAs in individual cells. Here, we present Epi-Impute, a computational method for dropout imputation by reconciling expression and epigenomic data. Epi-Impute leverages single-cell ATAC-seq data as an additional source of information about gene activity to reduce the number of dropouts. We demonstrate that Epi-Impute outperforms existing methods, especially for very sparse single-cell RNA-seq data sets, significantly reducing imputation error. At the same time, Epi-Impute accurately captures the primary distribution of gene expression across cells while preserving the gene-gene and cell-cell relationship in the data. Moreover, Epi-Impute allows for the discovery of functionally relevant cell clusters as a result of the increased resolution of scRNA-seq data due to imputation. |
| first_indexed | 2024-03-11T05:36:18Z |
| format | Article |
| id | doaj.art-df91d16a64bf4cbda6f0037133cd7d16 |
| institution | Directory Open Access Journal |
| issn | 1661-6596 1422-0067 |
| language | English |
| last_indexed | 2024-03-11T05:36:18Z |
| publishDate | 2023-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | International Journal of Molecular Sciences |
| spelling | doaj.art-df91d16a64bf4cbda6f0037133cd7d162023-11-17T16:48:11ZengMDPI AGInternational Journal of Molecular Sciences1661-65961422-00672023-03-01247622910.3390/ijms24076229Epi-Impute: Single-Cell RNA-seq Imputation via Integration with Single-Cell ATAC-seqMikhail Raevskiy0Vladislav Yanvarev1Sascha Jung2Antonio Del Sol3Yulia A. Medvedeva4Department of Biological and Medical Physics, Moscow Institute of Physics and Technology, 141701 Moscow, RussiaDepartment of Biological and Medical Physics, Moscow Institute of Physics and Technology, 141701 Moscow, RussiaComputational Biology Laboratory, Center for Cooperative Research in Biosciences, 48160 Derio, Bizkaia, SpainComputational Biology Laboratory, Center for Cooperative Research in Biosciences, 48160 Derio, Bizkaia, SpainDepartment of Biological and Medical Physics, Moscow Institute of Physics and Technology, 141701 Moscow, RussiaSingle-cell RNA-seq data contains a lot of dropouts hampering downstream analyses due to the low number and inefficient capture of mRNAs in individual cells. Here, we present Epi-Impute, a computational method for dropout imputation by reconciling expression and epigenomic data. Epi-Impute leverages single-cell ATAC-seq data as an additional source of information about gene activity to reduce the number of dropouts. We demonstrate that Epi-Impute outperforms existing methods, especially for very sparse single-cell RNA-seq data sets, significantly reducing imputation error. At the same time, Epi-Impute accurately captures the primary distribution of gene expression across cells while preserving the gene-gene and cell-cell relationship in the data. Moreover, Epi-Impute allows for the discovery of functionally relevant cell clusters as a result of the increased resolution of scRNA-seq data due to imputation.https://www.mdpi.com/1422-0067/24/7/6229single cell RNA-seqimputationsingle cell ATAC-seq |
| spellingShingle | Mikhail Raevskiy Vladislav Yanvarev Sascha Jung Antonio Del Sol Yulia A. Medvedeva Epi-Impute: Single-Cell RNA-seq Imputation via Integration with Single-Cell ATAC-seq International Journal of Molecular Sciences single cell RNA-seq imputation single cell ATAC-seq |
| title | Epi-Impute: Single-Cell RNA-seq Imputation via Integration with Single-Cell ATAC-seq |
| title_full | Epi-Impute: Single-Cell RNA-seq Imputation via Integration with Single-Cell ATAC-seq |
| title_fullStr | Epi-Impute: Single-Cell RNA-seq Imputation via Integration with Single-Cell ATAC-seq |
| title_full_unstemmed | Epi-Impute: Single-Cell RNA-seq Imputation via Integration with Single-Cell ATAC-seq |
| title_short | Epi-Impute: Single-Cell RNA-seq Imputation via Integration with Single-Cell ATAC-seq |
| title_sort | epi impute single cell rna seq imputation via integration with single cell atac seq |
| topic | single cell RNA-seq imputation single cell ATAC-seq |
| url | https://www.mdpi.com/1422-0067/24/7/6229 |
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