Alsaggaf, Ibrahim;
Buchan, Daniel;
Wan, Cen;
(2024)
Improving cell type identification with Gaussian noise-augmented single-cell RNA-seq contrastive learning.
Briefings in Functional Genomics
, 23
(4)
pp. 441-451.
10.1093/bfgp/elad059.
Preview |
Text
Buchan_draft_Proof.pdf - Accepted Version Download (11MB) | Preview |
Abstract
Cell type identification is an important task for single-cell RNA-sequencing (scRNA-seq) data analysis. Many prediction methods have recently been proposed, but the predictive accuracy of difficult cell type identification tasks is still low. In this work, we proposed a novel Gaussian noise augmentation-based scRNA-seq contrastive learning method (GsRCL) to learn a type of discriminative feature representations for cell type identification tasks. A large-scale computational evaluation suggests that GsRCL successfully outperformed other state-of-the-art predictive methods on difficult cell type identification tasks, while the conventional random genes masking augmentation-based contrastive learning method also improved the accuracy of easy cell type identification tasks in general.
| Type: | Article |
|---|---|
| Title: | Improving cell type identification with Gaussian noise-augmented single-cell RNA-seq contrastive learning |
| Location: | England |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1093/bfgp/elad059 |
| Publisher version: | http://dx.doi.org/10.1093/bfgp/elad059 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Contrastive learning, scRNA-seq, Cell type identification, Data augmentation |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10196830 |
Loading...
Loading...Loading...Loading...Archive Staff Only
 |
View Item |
