Learn how to apply machine learning to single-cell data. Random forest is a powerful machine learning classifier and a great tool for analyzing single-cell RNAseq data. In addition to predicting classifications, you can extract the gene importance from the model as a way to identify genes that describe your populations. Here I use several examples to show you how to use the random forest model in Python to do single-cell analyses.
Notebook:
github.com/mou...
Reference:
www.nature.com...
tabula-sapiens...
0:00 - Intro
1:10 - Basic RF usage
5:05 - Classifying cells in other data
12:15 - Classifying cells in same data
Негізгі бет Applying random forest classifiers to single-cell RNAseq data
No video
Пікірлер: 20