Hi everyone,

I calculated immune cell composition using the xCell immunedeconv method, but I realized the scale is quite large, approximately from 1e+18 to 1e-18. I would like to calculate immune cell ratios and compare them between case and control groups. I ran the Mann-Whitney test, but as expected, with these starting values, the ratios were extremely large, leading to downstream statistics and log fold change values in the range of millions.

I calculated lfc as: LFC= Mean(case) - Mean(controls)

Is there a way to normalize the data before calculating ratios and performing statistics to obtain more reasonable and interpretable results?

What data are you deconvoluting, does the data look ok before running deconvolution. Have you tried running some other test data, does it look the same afterwards?

I done deconvulation on TPM normalized counts data. On the same data I've done TIMER, MCP, CIBERSORT, but non of these shown the same problem. Even xCell had a good results before calculating ratios.

xCell output before statistics

xCell statistical results

But when I calculated ratios between immune cells i got following results, with huge differences in terms of lfc, variations etc. I would like to highlight that I calculated ratios as well for CIBERSORT,MCP and TIME output and I done statistical analysis using the same code.