Table 4.
Features of methods employing deep learning approach.
| Serial No. | Algorithm/Method | Interface | Programming Language | Link |
|---|---|---|---|---|
| 1 | AutoImpute | Linux | Python, R |
https://github.com/divyanshu-talwar/ AutoImpute |
| 2 | ScVI | Linux | Python | https://github.com/YosefLab/scVI |
| DCA | Linux | Python |
https://github.com/theislab/ dca |
|
| 3 | DeepImpute | Linux | Python | https://github.com/lanagarmire/DeepImpute |
| 4 | SAUCIE | Linux | Python | https://github.com/KrishnaswamyLab/SAUCIE/ |
| 5 | scScope | Linux | Python | https://github.com/AltschulerWu-Lab/scScope |
| 7 | deepMc | Linux, Windows | Matlab | https://drive.google.com/drive/folders/1TMD8sjPXlpe5V-3EAi38aFHQoy1gXd6h |
| 8 | Deconvolution through saliency maps | Linux | Python | https://gitlab.com/cphgeno/expression_saliency |
| 9 | LATE/TRANSLATE | Linux | Python | https://github.com/audreyqyfu/LATE |