Hello everyone,
I'm now trying to predict the different cell types from bulk RNA-seq data. Are there any algorithms or tools for this? I just remember once my ex-colleague mentioned that there is a deep-learning based algorithm but I forgot its name...
Maybe it's in this list of software for single cell data analysis.
It depends on what you mean by bulk but in principle, any machine learning algorithm can be applied. It's often a matter of finding a suitable data representation (e.g. for graph-based clustering). Most unsupervised approaches are based on dimensionality reduction (often PCA) followed by some classical clustering algorithm (e.g. k-means, hierarchical clustering). More recently, logistic regression is used in this paper and a neural network is used in this one.
Use of this site constitutes acceptance of our User Agreement and Privacy Policy.
version 2.3.6
Hi Jean-Karim Herich, thank you for your help. I am looking for the algorithms or tools that people can identify cell types from bulk RNA seq data instead of single cell data. But anyway, I'll check the list you provided and thank you again.
Then maybe what you're after are deconvolution methods like in the R package CellMix.