(colab)= # Run tutorials on Google Colab ## Wish to try Scarf without installation? Google Colab allows running Python code directly on Google's server through a notebook interface. With the following links you can try running any of the vignettes on Colab. This is a quick way to try Scarf without installing it. ## Before you run notebooks on Colab Paste the following code on the top of the notebook before running any other cell on Colab notebook !pip install ipython-autotime !pip install scarf !pip install -U numpy scipy Google Colab has older versions of Numpy and Scipy which are not compatible with Scarf. Once `scipy` and `numpy` have updated you will see a `RESTART RUNTIME` button. Click on it to activate latest versions. Now you are free to execute rest of the notebook. ## Colab links - [Basic workflow of Scarf using scRNA-Seq data](https://colab.research.google.com/github/parashardhapola/scarf_vignettes/blob/main/basic_tutorial_scRNAseq.ipynb) - [Workflow for analysis of scATAC-Seq count matrices](https://colab.research.google.com/github//parashardhapola/scarf_vignettes/blob/main/basic_tutorial_scATACseq.ipynb) - [Handling datasets with multiple modalities](https://colab.research.google.com/github/parashardhapola/scarf_vignettes/blob/main/multiple_modalities.ipynb) - [Cell subsampling using TopACeDo](https://colab.research.google.com/github/parashardhapola/scarf_vignettes/blob/main/cell_subsampling_tutorial.ipynb) - [Projection of cells across datasets](https://colab.research.google.com/github/parashardhapola/scarf_vignettes/blob/main/data_projection.ipynb) - [Merging datasets and partial training](https://colab.research.google.com/github/parashardhapola/scarf_vignettes/blob/main/merging_datasets.ipynb) - [Understanding how data is organized in Scarf](https://colab.research.google.com/github/parashardhapola/scarf_vignettes/blob/main/zarr_explanation.ipynb) - [Getting data in and out of Scarf](https://colab.research.google.com/github/parashardhapola/scarf_vignettes/blob/main/download_conversion.ipynb)