I'm not really following what you're talking about with pct1 and pct2, but the min.pct parameter just determines the fraction of cells in either group the feature has to be expressed in to be included in the analysis. It's meant to remove lowly expressed genes. So in your case, that'd mean for a gene to be included in the differential expression for cluster 1 (or 2, 3, etc) versus the other clusters, at least 25% of cells in cluster 1 or all other clusters must express the gene.
Hi Jared. Can you explain what does only.pos = TRUE argument does. I have been reading around this but couldn't find a concrete explanation for this argument. It was used in the following seurat issues: 1, 2, 3.
A similar question here went unanswered for years now.
FindAllMarkers function helps to identify gene markers for each cluster relative to all other clusters. The expression for a given gene among cells in a given cluster is compared against the expression of that gene among cells in all other clusters. In the output, pct.1 is the percentage of cells in the cluster where the gene is detected, while pct.2 is the percentage of cells on average in all the other clusters where the gene is detected. A gene to be considered as an IDEAL cluster marker is expected to be expressed exclusively in that cluster and silenced in all others and thus pct.1 will be more towards 1 and pct.2 towards 0.
Hi Jared. Can you explain what does
only.pos = TRUEargument does. I have been reading around this but couldn't find a concrete explanation for this argument. It was used in the followingseuratissues: 1, 2, 3. A similar question here went unanswered for years now.See
?FindMarkers.So it reports Marker genes with positive
avg_log2FCright?That is correct.