User: TriS
TriS • 4.2k
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Posts by TriS
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... part of the answer can be found here for Seurat:
https://www.biostars.org/p/409790/
for Scanpy's code (https://github.com/theislab/scanpy/blob/master/scanpy/tools/_rank_genes_groups.py):
method
The default method is `'t-test'`,
`'t-test_overestim_var'` overestimates variance of ...
written 10 weeks ago by
TriS • 4.2k
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... if those are the column names then you must have some sort of genes as row names. you gotta do a little bit of coding to define what genes belong to what cluster.
1- based on the cluster p.value and Log2FC define what belongs to what cluster
2- repeat that for all 20 clusters
3- color each gene base ...
written 10 months ago by
TriS • 4.2k
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... or if you want to put them all together you can just color each group differently.
library(ggplot2)
ggplot(macrphage_list, aes(x = untreated.Log2.Fold.Change, y = -log10(untreated.P.Value), fill = myClusters)) + geom_point(size = 3) + geom_hline(yinterecept=-log10(10e-5)) + geom_vline(xi ...
written 10 months ago by
TriS • 4.2k
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... this post is now pretty old, the data on cbioportal have been updated. that's why you see a difference ...
written 10 months ago by
TriS • 4.2k
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... see comments above where I addressed this question ...
written 18 months ago by
TriS • 4.2k
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... it's good practice to remove genes that have expression = 0 or very low expression in most samples. the % is up to you, this is an example, and I used 50% ...
written 18 months ago by
TriS • 4.2k
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... that's because you are trying to assign a variable starting with the square bracket, which in R is used to subset variables. I'd suggest to get familiar with R first, instead of copy-paste the code above. that will help you preventing lethal mistakes
...
written 18 months ago by
TriS • 4.2k
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... that will require quite a lil bit of coding, I'd suggest you to refine your question first and then contact a bioinformatician/statistician to help you coding it ...
written 18 months ago by
TriS • 4.2k
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... you have to select patients based on the expression of two genes.
- choose your two genes
- classify patients based on the expression of both (i.e. `tp53 > 2 & pi3k > 2`)
- that will be your altered class
- the rest is not altered.
or you can also count patients that are altered for one an ...
written 18 months ago by
TriS • 4.2k
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... this code is a guideline, not a copy and paste document. I'd suggest you to read a bit more about basic R usage and survival analysis before digging into this. it'll be time well spent ...
written 2.8 years ago by
TriS • 4.2k
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