Assign the result to an object named `seurat_markers_all`. What is the class of that object? How do you control the set of clusters that are used?```{r} seurat_markers_all <- FindAllMarkers(seurat_after_qc, only.pos = TRUE, #detect only positive markers ...
There are alternative ways to incorporate the Input controls. For example, instead of scaling the control read counts,the control libraries can be down-sampled to the same level as each corresponding ChIP sample prior to peak calling (MACS2 does this) and counting.This is what we do in our...
By default, the result() function will return the LRT test p-value and MLE log2FC for the difference between Mut vs WT at the last timepoints, controlling for baseline To get the log2FC for the difference between Mut vs WT at a different timepoint, you have to manually specify it, ...
Below is my code: #load the data with low read samples pruned out load("data/secondmito/lowreads_pruned/otutable_top10removed_coral_866_may.Rdata") #otu_tablef_no10_coralf_sm_866f_mayf ls() print(otu_tablef_no10_coralf_sm_866f_mayf) # 39 samples, 6037 taxa ...
Imagine that you have a gene whose expression is twice as high after treatment A than in the control condition. We would want the result of the comparison of this expression to be a Log(2) Fold Change of 1, not -1. By forming the contrast in line 14 as "'TreatmentA','Control'",...
But, since we don't know the actual source of the problem yet, we can keep it in mind. Note that I changed the title of this issue to reflect the problem encountered and not the loosely-inferred diagnosis, since we don't actually know yet what the problem is. Did you try specifying...