Artificial neural network system for cell classification using single cell RNA expression
We implemented an automated system for single-cell classification using artificial neural networks (ANN). Our system takes single-cell gene expression sparse matrices and trains ANN to classify cell types and subtypes. The assemblies of ANNs predict cell classes by voting. We tested the system in a...
| Main Authors: | , , , , , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2021
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| Subjects: | |
| Online Access: | https://eprints.nottingham.ac.uk/64682/ |
| _version_ | 1848800153528434688 |
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| author | Lin, Xin Zhong, Jiahui Lyu, Minjie Lin, Sen Keskin, Derin B. Zhang, Guanglan Brusic, Vladimir Chitkushev, Lou T. |
| author_facet | Lin, Xin Zhong, Jiahui Lyu, Minjie Lin, Sen Keskin, Derin B. Zhang, Guanglan Brusic, Vladimir Chitkushev, Lou T. |
| author_sort | Lin, Xin |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | We implemented an automated system for single-cell classification using artificial neural networks (ANN). Our system takes single-cell gene expression sparse matrices and trains ANN to classify cell types and subtypes. The assemblies of ANNs predict cell classes by voting. We tested the system in a case study where we trained ANNs with a dataset containing approximately 120,000 single cells and tested the resulting model using an independent data set of 13,000 single cells. The overall accuracy of the 5-class classification was 95%. We trained and tested a total of 100 ANNs in 10 cycles. The prediction system demonstrated excellent reproducibility. The analysis of misclassifications indicated that 2% were likely classification errors, while the remaining 3% were likely due to mislabeled types and subtypes in the test set. |
| first_indexed | 2025-11-14T20:47:02Z |
| format | Conference or Workshop Item |
| id | nottingham-64682 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T20:47:02Z |
| publishDate | 2021 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-646822021-03-10T06:26:53Z https://eprints.nottingham.ac.uk/64682/ Artificial neural network system for cell classification using single cell RNA expression Lin, Xin Zhong, Jiahui Lyu, Minjie Lin, Sen Keskin, Derin B. Zhang, Guanglan Brusic, Vladimir Chitkushev, Lou T. We implemented an automated system for single-cell classification using artificial neural networks (ANN). Our system takes single-cell gene expression sparse matrices and trains ANN to classify cell types and subtypes. The assemblies of ANNs predict cell classes by voting. We tested the system in a case study where we trained ANNs with a dataset containing approximately 120,000 single cells and tested the resulting model using an independent data set of 13,000 single cells. The overall accuracy of the 5-class classification was 95%. We trained and tested a total of 100 ANNs in 10 cycles. The prediction system demonstrated excellent reproducibility. The analysis of misclassifications indicated that 2% were likely classification errors, while the remaining 3% were likely due to mislabeled types and subtypes in the test set. 2021-01-13 Conference or Workshop Item PeerReviewed application/pdf en cc_by https://eprints.nottingham.ac.uk/64682/1/Xin-BIBM-2020-cameraready.pdf Lin, Xin, Zhong, Jiahui, Lyu, Minjie, Lin, Sen, Keskin, Derin B., Zhang, Guanglan, Brusic, Vladimir and Chitkushev, Lou T. (2021) Artificial neural network system for cell classification using single cell RNA expression. In: 2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 16-19 Dec. 2020, Seoul, Korea (South). ANN automation of cell classification gene expression PBMC prediction system supervised machine learning http://dx.doi.org/10.1109/BIBM49941.2020.9313498 10.1109/BIBM49941.2020.9313498 10.1109/BIBM49941.2020.9313498 10.1109/BIBM49941.2020.9313498 |
| spellingShingle | ANN automation of cell classification gene expression PBMC prediction system supervised machine learning Lin, Xin Zhong, Jiahui Lyu, Minjie Lin, Sen Keskin, Derin B. Zhang, Guanglan Brusic, Vladimir Chitkushev, Lou T. Artificial neural network system for cell classification using single cell RNA expression |
| title | Artificial neural network system for cell classification using single cell RNA expression |
| title_full | Artificial neural network system for cell classification using single cell RNA expression |
| title_fullStr | Artificial neural network system for cell classification using single cell RNA expression |
| title_full_unstemmed | Artificial neural network system for cell classification using single cell RNA expression |
| title_short | Artificial neural network system for cell classification using single cell RNA expression |
| title_sort | artificial neural network system for cell classification using single cell rna expression |
| topic | ANN automation of cell classification gene expression PBMC prediction system supervised machine learning |
| url | https://eprints.nottingham.ac.uk/64682/ https://eprints.nottingham.ac.uk/64682/ https://eprints.nottingham.ac.uk/64682/ |