scIBD: a self-supervised iterative-optimizing model for boosting the detection of heterotypic doublets in single-cell chromatin accessibility data
Abstract Application of the widely used droplet-based microfluidic technologies in single-cell sequencing often yields doublets, introducing bias to downstream analyses. Especially, doublet-detection methods for single-cell chromatin accessibility sequencing (scCAS) data have multiple assay-specific...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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BMC
2023-10-01
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| Series: | Genome Biology |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13059-023-03072-y |
| _version_ | 1797559361953857536 |
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| author | Wenhao Zhang Rui Jiang Shengquan Chen Ying Wang |
| author_facet | Wenhao Zhang Rui Jiang Shengquan Chen Ying Wang |
| author_sort | Wenhao Zhang |
| collection | DOAJ |
| description | Abstract Application of the widely used droplet-based microfluidic technologies in single-cell sequencing often yields doublets, introducing bias to downstream analyses. Especially, doublet-detection methods for single-cell chromatin accessibility sequencing (scCAS) data have multiple assay-specific challenges. Therefore, we propose scIBD, a self-supervised iterative-optimizing model for boosting heterotypic doublet detection in scCAS data. scIBD introduces an adaptive strategy to simulate high-confident heterotypic doublets and self-supervise for doublet-detection in an iteratively optimizing manner. Comprehensive benchmarking on various simulated and real datasets demonstrates the outperformance and robustness of scIBD. Moreover, the downstream biological analyses suggest the efficacy of doublet-removal by scIBD. |
| first_indexed | 2024-03-10T17:44:17Z |
| format | Article |
| id | doaj.art-d4b86c163bbe4e86bd51e3f8e8da7b16 |
| institution | Directory Open Access Journal |
| issn | 1474-760X |
| language | English |
| last_indexed | 2024-03-10T17:44:17Z |
| publishDate | 2023-10-01 |
| publisher | BMC |
| record_format | Article |
| series | Genome Biology |
| spelling | doaj.art-d4b86c163bbe4e86bd51e3f8e8da7b162023-11-20T09:35:18ZengBMCGenome Biology1474-760X2023-10-0124112810.1186/s13059-023-03072-yscIBD: a self-supervised iterative-optimizing model for boosting the detection of heterotypic doublets in single-cell chromatin accessibility dataWenhao Zhang0Rui Jiang1Shengquan Chen2Ying Wang3Department of Automation, Xiamen UniversityMinistry of Education Key Laboratory of Bioinformatics, Research Department of Bioinformatics at the Beijing National Research Center for Information Science and Technology, Center for Synthetic and Systems Biology, Department of Automation, Tsinghua UniversitySchool of Mathematical Sciences and LPMC, Nankai UniversityDepartment of Automation, Xiamen UniversityAbstract Application of the widely used droplet-based microfluidic technologies in single-cell sequencing often yields doublets, introducing bias to downstream analyses. Especially, doublet-detection methods for single-cell chromatin accessibility sequencing (scCAS) data have multiple assay-specific challenges. Therefore, we propose scIBD, a self-supervised iterative-optimizing model for boosting heterotypic doublet detection in scCAS data. scIBD introduces an adaptive strategy to simulate high-confident heterotypic doublets and self-supervise for doublet-detection in an iteratively optimizing manner. Comprehensive benchmarking on various simulated and real datasets demonstrates the outperformance and robustness of scIBD. Moreover, the downstream biological analyses suggest the efficacy of doublet-removal by scIBD.https://doi.org/10.1186/s13059-023-03072-ySingle-cellChromatin accessibilityDoubletsDetection |
| spellingShingle | Wenhao Zhang Rui Jiang Shengquan Chen Ying Wang scIBD: a self-supervised iterative-optimizing model for boosting the detection of heterotypic doublets in single-cell chromatin accessibility data Genome Biology Single-cell Chromatin accessibility Doublets Detection |
| title | scIBD: a self-supervised iterative-optimizing model for boosting the detection of heterotypic doublets in single-cell chromatin accessibility data |
| title_full | scIBD: a self-supervised iterative-optimizing model for boosting the detection of heterotypic doublets in single-cell chromatin accessibility data |
| title_fullStr | scIBD: a self-supervised iterative-optimizing model for boosting the detection of heterotypic doublets in single-cell chromatin accessibility data |
| title_full_unstemmed | scIBD: a self-supervised iterative-optimizing model for boosting the detection of heterotypic doublets in single-cell chromatin accessibility data |
| title_short | scIBD: a self-supervised iterative-optimizing model for boosting the detection of heterotypic doublets in single-cell chromatin accessibility data |
| title_sort | scibd a self supervised iterative optimizing model for boosting the detection of heterotypic doublets in single cell chromatin accessibility data |
| topic | Single-cell Chromatin accessibility Doublets Detection |
| url | https://doi.org/10.1186/s13059-023-03072-y |
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