Applying #MachineLearning to single-cell data can seem daunting - so i've started a video series to help people get going. Starting with a Random Forest classifier, I give several #Python examples for predicting cell states: youtu.be/3Q9R2mv6GO0 #bioinformatics
what are the current methods to determine the optimal number of clusters from a single-cell RNAseq dataset?
Tweetorial / remarks about our mega ocular single cell "scEiaD" resource: biorxiv.org/content/10.110……, github.com/davemcg/scEiaD. In June 2019 I simultaneously decided that I would go Genome Informatics 2019 and It was time to make the single-cell update to eyeIntegration.nei.nih.gov
![](http://atlasappimages.s3.amazonaws.com/production/users/27/thumb/IMG_7406.jpg?1618320999)
- Tweetorial on scEiaD (eye in a dish)
- They used scarches to integrate LOADS of datasets and have a google colab notebook of it all
- Also metrics for assessing integration and methods for scarches hyperparameter optimisation
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