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@@ -12,11 +12,11 @@ The Dorado Basecalling workflow is used to convert Oxford Nanopore `POD5` sequen | |
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### Model Type Selection | ||
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Users can choose between automatic or manual model selection using a configurable use_auto_model flag: | ||
Users can configure the basecalling model by setting the dorado_model input parameter: | ||
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Automatic Model Selection: Automatically picks the best model ('sup', 'hac', or 'fast') based on the input file and user-defined model accuracy paramater. | ||
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Manual Model Input: If the user disables automatic selection, a specific model path or model version must be provided. | ||
- Default Model: "sup" (super accuracy) is used unless overridden by the user. | ||
- Manual Model Input: Users can specify the full path or name of a specific model (e.g., [email protected]). | ||
- Automatic Detection: When set to sup, hac, or fast, Dorado will automatically select the appropriate model version if available. | ||
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- **Model Type (sup):** (super accuracy) The most accurate model, recommended for critical applications requiring the highest basecall accuracy. It is the slowest of the three model types. | ||
- **Model Type (hac):** (High Accuracy) A balance between speed and accuracy, recommended for most users. Provides accurate results faster than `sup` but less accurate than `sup`. | ||
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@@ -42,10 +42,8 @@ Manual Model Input: If the user disables automatic selection, a specific model p | |
| **Task** | **Variable** | **Type** | **Description** | **Default Value** | **Required** | | ||
|---|---|---|---|---|---| | ||
| Basecalling | **input_files** | Array[File] | Array of `POD5` files for basecalling | None | Yes | | ||
| Basecalling | **use_auto_model** | Boolean | Use automatic model selection (`sup`, `hac`, or `fast` based on model accuracy)| true | No | | ||
| Basecalling | **model_accuracy** | String | Desired model accuracy (`sup`, `hac`, `fast`) if using automatic selection | sup | No | | ||
| Basecalling | **dorado_model** | Boolean | Model accuracy or full model name (default: 'sup')| sup | No | | ||
| Basecalling | **fastq_file_name** | String | Prefix for naming output FASTQ files | None | Yes | | ||
| Basecalling | **dorado_model** | String | Model type (e.g., `[email protected]`) if manual input | None | Yes | | ||
| Basecalling | **kit_name** | String | Sequencing kit name used (e.g., `SQK-RPB114-24`). | None | Yes | | ||
| Basecalling | **cpu** | Int | Number of CPUs allocated | 8 | No | | ||
| Basecalling | **memory** | String | Amount of memory to allocate | 32GB | No | | ||
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@@ -59,6 +57,8 @@ Manual Model Input: If the user disables automatic selection, a specific model p | |
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### Detailed Input Information | ||
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- **dorado_model**: If set to 'sup', 'hac', or 'fast', the workflow will run with automatic model selection. If a full model name is provided, Dorado will use that model directly. | ||
- **fastq_file_name**: This will serve as a prefix for the output FASTQ files. For example, if you provide `project001`, the resulting files will be named `project001_barcodeXX.fastq.gz`. | ||
- **kit_name**: Ensure the correct kit name is provided, as it determines the barcoding and adapter trimming behavior. | ||
- **fastq_upload_path**: This is the folder path in Terra where the final FASTQ files will be transferred for further analysis. Ensure the path matches your Terra workspace configuration. | ||
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