Question: Seurat "FindMarkers" and "FindallMarkers" v.s. Scanpy "rank_genes_groups"
0
gravatar for krorange
7 weeks ago by
krorange0
krorange0 wrote:

I am processing the same dataset with both Seurat and Scanpy. In Seurat, I got 3 clusters and cluster 2 seems like the target cell type; I got 2 clusters in Scanpy and cluster 1 seems like the target. I am trying to get the marker genes that shows up in both target clusters. But I have two questions...

  1. My understanding is that if I didn't specify ident.2 in Seurat's "FindMarkers", Seurat will find the marker genes comparing the ident.1=0 to the rest, am I right? If so, what's the difference between FindMarkers(object = dataa, ident.1 = 2, min.pct = 0.25), FindMarkers(object = dataa, ident.1 = 2, ident.2 = c(0, 1), min.pct = 0.25) and FindAllMarker(object=dataa, min.pct=0.25)?

  2. Since I'm comparing Seurat result with Scanpy's "sc.tl.rank_genes_groups", which processing method in question 1 should I compare with?

I'm really confused, it would be helpful if someone can explain these to me.

Thank you so much!

scanpy seurat scrna R single-cell • 299 views
ADD COMMENTlink modified 5 weeks ago by TriS4.2k • written 7 weeks ago by krorange0
0
gravatar for TriS
5 weeks ago by
TriS4.2k
United States, Buffalo
TriS4.2k wrote:

part of the answer can be found here for Seurat: FindConservedMarkers vs FindMarkers vs FindAllMarkers Seurat

for Scanpy's code (https://github.com/theislab/scanpy/blob/master/scanpy/tools/_rank_genes_groups.py):

method
    The default method is `'t-test'`,
    `'t-test_overestim_var'` overestimates variance of each group,
    `'wilcoxon'` uses Wilcoxon rank-sum,
    `'logreg'` uses logistic regression. See [Ntranos18]_,
    `here <https://github.com/theislab/scanpy/issues/95>`__ and `here
    <http://www.nxn.se/valent/2018/3/5/actionable-scrna-seq-clusters>`__,
    for why this is meaningful.

looks like the approaches are not that different, and Scanpy's rank_genes_group is similar to Seurat FindMarkers

ADD COMMENTlink modified 5 weeks ago • written 5 weeks ago by TriS4.2k
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