I am using FindMarkers to identify significant differential accessible peaks from scATAC-seq data. We are using min.pct = 0.05 and logfc.threshold = 0.25 as cut-offs. However, this analysis obviously ignores all sites that are shared (logfc.threshold < 0.25). We are interested in also knowing the number of peaks that are shared between the two groups, i.e. those with a min.pct = 0.05, but not significantly different:
However, this test would take us nearly 2 hours to run, just to get the list of peaks with a min.pct = 0.05. Is there a way to pull this information before passing it to FindMarkers for differential testing?
Hi Tim,
I work with Minjun. The FoldChange function is actually better than what we were originally planning.
Thank you for pointing us in the right direction!
Jeff
Hi Tim,
I am using FindMarkers to identify significant differential accessible peaks from scATAC-seq data. We are using min.pct = 0.05 and logfc.threshold = 0.25 as cut-offs. However, this analysis obviously ignores all sites that are shared (logfc.threshold < 0.25). We are interested in also knowing the number of peaks that are shared between the two groups, i.e. those with a min.pct = 0.05, but not significantly different:
FindMarkers(data, ident.1 = "ident1", ident.2 = "ident2", min.pct = 0.05, assay = "peaks", test.use = "LR", latent.vars = "peak_region_fragments", logfc.threshold = 0)
However, this test would take us nearly 2 hours to run, just to get the list of peaks with a min.pct = 0.05. Is there a way to pull this information before passing it to FindMarkers for differential testing?
Thank you,
Minjun