WNN in Seurat

Dear all,

I am trying to follow the WNN vignette here
satijalab.org/seurat/articles/weighted_nearest_neighbor_analysis.html

After the steps below, I would like to annotate my clusters, hence I need to know the markers which best represent each cluster.

pbmc <- FindMultiModalNeighbors(pbmc, reduction.list = list(“pca”, “lsi”), dims.list = list(1:50, 2:50))
pbmc <- RunUMAP(pbmc, nn.name = “weighted.nn”, reduction.name = “wnn.umap”, reduction.key = “wnnUMAP_”)
pbmc <- FindClusters(pbmc, graph.name = “wsnn”, algorithm = 3, verbose = FALSE)

So I go on to do

allmarkers <- FindAllMarkers(pbmc)

However, I am unsure how to interpret the findings. Below is the allmarkers object, which is calculated from ATAC assay counts, since the last default assay was set to “ATAC” with DefaultAssay(pbmc) <- “ATAC”.
Is there any way to find the genes or chromatin peaks most associated with the clusters coming out from the WNN graph that combines both RNAseq and ATACseq?

Thanks in advance.

head(allmarkers)

                            p_val avg_log2FC pct.1 pct.2 p_val_adj cluster

chr1-186828497-186829311 1.242405e-06 -0.4548612 0.025 0.162 0.1287653 0
chr1-42462733-42463616 6.747624e-06 -0.3321175 0.130 0.302 0.6993372 0
chr19-11505637-11505933 1.287234e-05 0.3955261 0.365 0.210 1.0000000 0
chr3-112858127-112859021 1.368274e-05 -0.4490370 0.065 0.202 1.0000000 0
chr9-129482422-129483279 1.468715e-05 0.4140303 0.300 0.154 1.0000000 0
chr7-18221372-18222277 1.476420e-05 -0.5840315 0.025 0.135 1.0000000 0
gene
chr1-186828497-186829311 chr1-186828497-186829311
chr1-42462733-42463616 chr1-42462733-42463616
chr19-11505637-11505933 chr19-11505637-11505933
chr3-112858127-112859021 chr3-112858127-112859021
chr9-129482422-129483279 chr9-129482422-129483279
chr7-18221372-18222277 chr7-18221372-18222277

Read more here: Source link