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- 🐛 use larger image to test tutorial on colab
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Henry committed May 30, 2024
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2 changes: 1 addition & 1 deletion .github/workflows/test_pkg_on_colab.yaml
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Expand Up @@ -11,7 +11,7 @@ on:
jobs:
test-tutorial-on-colab:
name: Test tutorial on latest colab image
runs-on: ubuntu-latest-2core # increase disk space
runs-on: ubuntu-latest-4core # increase disk space
# https://console.cloud.google.com/artifacts/docker/colab-images/europe/public/runtime
container:
image: europe-docker.pkg.dev/colab-images/public/runtime:latest
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14 changes: 14 additions & 0 deletions project/README.md
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Expand Up @@ -204,3 +204,17 @@ jupytext 00_5_training_data_exploration.py --to ipynb -o - | papermill - runs/ex
- finds files originationg from fractionation experiments
- plot mask indicating presence/abscence of peptide measurement in an experiment
- intensity log-transformation:

## Adhoc analysis

Compare performance splitting samples into train, validation and test set.
Use scikit-learn `KNN_IMPUTER` as it's easiest to tweak and understand.

```bash
# classic:
jupytext --to ipynb -k - -o - 01_1_train_KNN.py | papermill - runs/rev3/01_1_train_KNN.ipynb
# train only on samples without simulated missing values, add simulated missing values to test and validation samples
jupytext --to ipynb -k - -o - 01_1_train_KNN_unique_samples.py | papermill - runs/rev3/01_1_train_KNN_unique_samples.ipynb
# new comparison (check if the old nb could be used for this purpose)
jupytext --to ipynb -k - -o - 01_3_revision3.py | papermill - runs/rev3/01_3_revision3.ipynb
```
23 changes: 23 additions & 0 deletions project/config/single_dev_dataset/proteinGroups_N50/README.md
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# Config files

## Version 1 imputation workflow

For [`worflow/Snakefile`](https://github.com/RasmussenLab/pimms/blob/HEAD/project/workflow/Snakefile)

```bash
config.yaml # main config
split.yaml # split data config referenced in config.yaml
train_CF.yaml # CF train config referenced in config.yaml
train_DAE.yaml # DAE train config referenced in config.yaml
train_KNN.yaml # KNN train config referenced in config.yaml
train_Median.yaml # Median train config referenced in config.yaml
train_VAE.yaml # VAE train config referenced in config.yaml
```

## Version 2 impuation workflow

For [`workflow/Snakefile_v2.yaml`](https://github.com/RasmussenLab/pimms/blob/HEAD/project/workflow/Snakefile_v2.smk) only one config file is needed:

```bash
config_v2.yaml
```

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