Entering edit mode
3.6 years ago
BenHu • 0
I have downloaded a public expression matrix for a scRNA-seq. Does anyone know how to perform Gene-Gene Co-expression, like this paper Molecular Diversity and Specializations among the Cells of the Adult Mouse Brain. Best,
if I know how to do that, I wouldn't ask this question.
Hello, which part, specifically, are you finding it difficult to follow? I took a closer look myself and can deduce the following rough steps to help you get started:
Step 1 - filtering
Step 2 - ICA (independent component analysis)
Step 3 - KNN clustering
Perform clustering on the 60 ICA components using the cluster implementation in Seurat. Basically, re-use Seurat's functions
FindClusters(). I use these in a function in a package that I'm currently developing, to give you an idea: https://github.com/kevinblighe/scToolkit/blob/master/R/clusKNN.R
That should bring you up to the line "To identify finer substructure among these classes, classes with more than 200 cells were selected for subclustering", whereby they then commence a second round of ICA on a finer subset of genes, it seems.
Unfortunately, following bioinformatics methods can be a nightmare, because it is impossible to accurately write in English language the minute details that are required to comprise a comprehensive methodology.
You might also want to take a look at this article to get ideas for alternatives to pearson correlation.