This presentation really helped with my Master Thesis. It is so much more informative to work with modules of DEGs than just investigating single genes...
I swear, no matter how much I try to intuitively understand eigengenes I fail miserably. I wonder how you go from your expression data to a (eigene?) value for each module at each sample, which is the output you get when you run the code.
Module eigengene is the first principal component of the genes in that module. In intuitive terms, it is the made-up gene that represents all genes in that module the best. If you want to understand principal component analysis I recommend statquest's video on that on youtube.
This presentation really helped with my Master Thesis. It is so much more informative to work with modules of DEGs than just investigating single genes...
just want to say great lecture. really appreciate this.
Thanks for putting the course material and lecture online! One question... is the second part of this lecture available as a video on RUclips?
I still haven't finished but the introduction looks so promising. I will watch it later. Hope to have more discussion later.
Wonderful explanation
Hi. I really enjoyed the lecture. Where do I find the second half? Thank you.
Nice lecture!
Excellent.
Is this better than Cytoscape?
really powerful tool!!!
+whiteorchidfaye are you using it for RNA seq?
@@JohnWayneGao you can use it with rna seq after normalization
I swear, no matter how much I try to intuitively understand eigengenes I fail miserably. I wonder how you go from your expression data to a (eigene?) value for each module at each sample, which is the output you get when you run the code.
Module eigengene is the first principal component of the genes in that module. In intuitive terms, it is the made-up gene that represents all genes in that module the best. If you want to understand principal component analysis I recommend statquest's video on that on youtube.
Sir I need next part video links
ruclips.net/video/4h0_izP6ab0/видео.html here you go mate