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Hello, I'm working with scRNA-seq data. I'm trying to extract the plotting information from plotCellTypeProps by accessing that object's $data so that I can use those cell proportions when making a customized ggplot box-and-whisker plot of cell proportions. The problem is that I want to append the
Immprops will be used to store the different proportions per cluster and I append Disease subgroup (Control vs Diseased.1 vs Diseased.2) for each patient to that to dodge my box-and-whisker plot later on.
I use bloodImmprops as the prop.list for the propeller.ttest/anova function. rownames([email protected]) are individual cells
The problem is that when I calculate the mean per each unique Cluster + Disease status combination, they are different than the means generated from propeller.ttest/anova and thus do not make sense when I visualize the ggplot with the manually-added p-values.
The bold text is the mean calculated from the plotCellTypeProps data. So for the proportions, Control = 0.084 and Disease = 0.089
Here is the output of the simple propeller function:
We can see that the mean proportions are very similar to the ones I extracted and summarized from the plotCellTypeProp data.
But, when I run propeller.ttest or propeller.anova, I get different means for my groups...
This is the output of propeller.ttest between Control and Disease for cluster 11 - Blood. As we can see, the proportions here differ if different directions since Control = 0.09 and Disease = 0.087
How can this be fixed?
The text was updated successfully, but these errors were encountered:
Hello, I'm working with scRNA-seq data. I'm trying to extract the plotting information from plotCellTypeProps by accessing that object's $data so that I can use those cell proportions when making a customized ggplot box-and-whisker plot of cell proportions. The problem is that I want to append the
pbloodImm <- plotCellTypeProps(clusters = bloodImm$RNA_snn_res.0.8, sample = bloodImm$Patient_ID)
Immprops <- pbloodImm$data
The problem is that when I calculate the mean per each unique Cluster + Disease status combination, they are different than the means generated from propeller.ttest/anova and thus do not make sense when I visualize the ggplot with the manually-added p-values.
Here is the output of the simple propeller function:
But, when I run propeller.ttest or propeller.anova, I get different means for my groups...
How can this be fixed?
The text was updated successfully, but these errors were encountered: