Entering edit mode
6.5 years ago
Tania
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180
Hi Everyone
I am confused with these rnaseq deonvolution, or maybe it is the first time to do rnaseq deconvolution, What I understand from the figure is that the 12 immune cells from top in the first figure are needed to defend tumor. They are positive in controls and lacking in most of the tumors. (They are not matched control-tumors). Is this what we get from this deonvolution ?
https://ibb.co/ePMxi8 and https://ibb.co/eUbBbT
I am not plotting the pvalues. Thanks
Deconvolution algorithm is used to estimate the relative abundance of a cell type in the sample. Thus, it's always >=0. You should always label your color bar, so that people can understand the result.
Fig2 maybe the plot of the raw data from RNAseq deconvolution results. But Fig1, the data must be processed, since it contains negative values.
FIG2 IS correlation plot. I was not sure which plot is better to do. Thanks for this illustration, I will update the figures.
Since I'm not in this field, could you explain what that corr fig means? why all diagonal are 1? eg, the first block (adipocyte, ctrl1) value =1, which indicates adipocyte are perfect corr with ctrl1. What's this mean?
I just tried to plot the data as a correlation, instead of heatmap and clustering. I was trying to figure out how to get any info from the deconvolution numbers. So, I was trying to say that all the controls not only ctr1 or 2 has a high correlation with this specific cell But it seems this is not what the actual data means. How to you usually present the deconvolution results?
You may get some idea from this paper:
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5906687/
That paper is really interesting and have nice plots. Thanks a lot :)