The source code for the reproducibility of "A versatile single-cell cross-modality translation method via dual-aligned variational autoencoders".
We also provide a software of scButterfly and a detailed tutorial and document.
experiment # experiemnt for scButterfly
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|---RNA_ATAC # translation between RNA and ATAC profiles
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| |---batch_correction_step # add batch correction step before training model
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| | |---paired_data # add batch correction step for paired data
| | |---unpaired_data # add batch correction step for unpaired data
| | |---simulated_data # simulating data with higher batch effects based on the CL dataset
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| |---CCA_anchors # data augmentation incorporating with CCA anchors
| |---cross_validation_by_cell # five-fold cross-validation by cell
| |---cross_validation_by_celltype # three-fold cross-validation by cell type
| |---cross_validation_by_batch # four-fold cross-validation by batch
| |---data_enhancement # data enhancement on the MK and MB datasets
| |---defense_noise # anti-noise experiment on the MCC dataset
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| |---down_sampling # down sampling for dataset
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| | |---cells # down sampling for cells on the MCC dataset
| | |---features # down sampling for features on the CL dataset
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| |---GO_analysis # gene ontology analysis on the MDS dataset
| |---integrative_analysis # integrative analysis in the BMMC dataset
| |---SNPsea_analysis # SNPsea analysis for translated profiles on the PBMC dataset
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| |---sensitive_analyses # sensitive analyses for multiple hyperparameters
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| | |---augmented_count # cell count of data augmentation
| | |---epochs_patience # pretraining epochs, integrative training epochs, and patience for early-stop
| | |---loss_weights # four weights for loss calculation
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| |---TF_regulatory_network_inference # TF regulatory network inference with DeepTFni on the PBMC dataset
| |---unpaired_data # five-fold cross-validation with unpaired data
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|---RNA_ADT # translation between RNA and ADT profiles
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| |---consecutive_translation # consecutive translation from ATAC to RNA to ADT
| |---cross_validation_by_cell # five-fold cross-validation by cell
| |---cross_validation_by_batch # cross-validation by batch
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|---Perturbational_responses # translation between single-cell perturbation responses
We provide reproducible methods through .sh and .ipynb files in each folder.