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update readme
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README.md

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@@ -28,6 +28,19 @@ discovery. Any method that can predict a modality from another must have
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accounted for these regulatory processes, but the demand for multi-modal
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data shows that this is not trivial.
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## Authors & contributors
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| name | roles |
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|:-------------------|:-------------------|
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| Alejandro Granados | author |
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| Alex Tong | author |
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| Bastian Rieck | author |
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| Daniel Burkhardt | author |
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| Kai Waldrant | contributor |
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| Kaiwen Deng | contributor |
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| Louise Deconinck | author |
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| Robrecht Cannoodt | author, maintainer |
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## API
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``` mermaid
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| Name | Type | Description |
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|:---|:---|:---|
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| `--input_train_mod1` | `file` | The mod1 expression values of the train cells. |
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| `--input_train_mod2` | `file` | The mod2 expression values of the train cells. |
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| `--input_train_mod1` | `file` | (*Optional*) The mod1 expression values of the train cells. |
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| `--input_train_mod2` | `file` | (*Optional*) The mod2 expression values of the train cells. |
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| `--input_test_mod1` | `file` | The mod1 expression values of the test cells. |
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| `--input_model` | `file` | A pretrained model for predicting the expression of one modality from another. |
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| `--output` | `file` | (*Output*) A prediction of the mod2 expression values of the test cells. |
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| `uns["gene_activity_var_names"]` | `string` | (*Optional*) Names of the gene activity matrix. |
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</div>
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