Update example code

README.md

@@ -14,25 +14,29 @@ Cellij (pronounced as "zillīj", derived from [Zellij](https://en.wikipedia.org/
     <img src="https://github.com/bioFAM/cellij/blob/main/docs/_static/figure1_black.png" alt="schematic" width="750"/>
 </p>
 
-Cellij is designed for rapid prototyping of custom factor analysis models, allowing users to efficiently define new models in an iterative fashion.
+Cellij is designed for rapid prototyping of custom factor analysis models, allowing users to efficiently define new models in an iterative fashion. The following code snippet shows an example how to setup and train a model with a predefined sparsity prior.
 ```python
-# First we create an instance of a MOFA class
-model = cellij.core.models.MOFA(n_factors=30, sparsity_prior="Horseshoe")
+mdata = cellij.Importer().load_CLL()
 
-# Afterwards, we need to add the data to the model
-model.add_data(data=mdata)
+# 1. We create a new Factor Analysis model
+model = cellij.FactorModel(n_factors=10)
 
-# We call `.fit` to train the model
-model.fit(
-    likelihoods={
-        "mrna": "Normal",
-        "mutations": "Bernoulli",
+# 2. We add an MuData object to the model
+model.add_data(mdata)
+
+# 3. We can add some options if we wish
+model.set_model_options(
+    weight_priors={
+        "drugs": "Horseshoe",
+        "methylation": "Horseshoe",
+        "mrna": "Horseshoe",
     },
-    epochs=1000,
-    learning_rate=0.001,
 )
+
+# 4. We train the model
+model.fit(epochs=10000)
 ```
-For a basic tutorial on real-world data, have a look at [this notebook](https://github.com/bioFAM/cellij/blob/main/notebooks/basic_example_mofa.ipynb).
+For basic tutorials on real-world data, please have a look at [our notebook repository]([https://github.com/bioFAM/cellij/blob/main/notebooks/basic_example_mofa.ipynb](https://github.com/bioFAM/cellij-notebooks/tree/main)).
 
 
 ## Getting started