Statistical test on Single-cell clusters(cell types)
1
0
Entering edit mode
9 months ago
David_emir ▴ 390

Hi All,

I have identified 5 different cell types from a single cell cluster, we have also identified a number of cells present in each condition(i.e. in Normal and Tumor clusters). I wanted to conduct statistical testing of differences in Gini coefficients between tumour and non-malignant compartments across all phenotypic clusters using exact permutation testing. I am unable to conduct this test, Please help me in conducting this test on my cell types. how best i can do this? i am very confused.

Thanks a lot for your kind help.

Stay safe, Dave.

enter image description here

statistical single cell exact permutation test • 402 views
ADD COMMENT
1
Entering edit mode
9 months ago

Hey David / Dave,

Please clarify:

  • you say 5 cell-types but there are 15 in your table
  • what values are these in your table?
  • where are your Gini coefficients? - another metric, like mean decrease accuracy, may be more readily-interpretable.
  • how did you produce the Gini coefficients?

As usual, please show all code that you have used.

ADD COMMENT
0
Entering edit mode

Hi Kevin, Sorry for that not so clear question. I have 5-cell types identified (the excell snapshot is just for the illustration) - B-cell, Myeloid cell, T-cell, Epithelial, Stromal cell. and according to this paper they conducted Statistical comparisons of Gini coefficients across compartments using Wilcoxon signed-rank test with Benjamini-Hochberg correction for multiple testing; statistical testing of differences in Gini coefficients between tumour and non-malignant compartments across all phenotypic clusters was also done by the authors using exact permutation testing. I wanted to conduct the same analysis on my cell types, but I was clueless on how to apply the same test on my data. Can you please help me? The values I am considering is the cell counts(No of cells) in Tumor and normal. Thanks, Dave

ADD REPLY
1
Entering edit mode

It is not readily clear what they did. A Wilcoxon signed rank exact test can be easily performed in R like this:

a <- rexp(1000, rate=.1)
b <- rexp(1000, rate=.1)

wilcox.test(a,b,paired=TRUE, exact=TRUE)

        Wilcoxon signed rank exact test

data:  a and b
V = 248875, p-value = 0.8805
alternative hypothesis: true location shift is not equal to 0

This test is already doing permutation in order to calculate the exact p-value. If you are unsure, I suggest posting on a a forum dedicated to statistics, or contact the authors of the published work.

ADD REPLY
0
Entering edit mode

Thanks a lot for your help Kevin, so in. my case the inputs would be no of cells in a particular cell type , say CD4-TREG cell count in Normal would be my a=423 ?

ADD REPLY
0
Entering edit mode

I thought that they were comparing Gini coefficients?

ADD REPLY

Login before adding your answer.

Traffic: 1375 users visited in the last hour
Help About
FAQ
Access RSS
API
Stats

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.

Powered by the version 2.3.6