Question: Seurat FindMarkers avg_logFC for integrated dataset
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gravatar for Payal
5 months ago by
Payal100
Payal100 wrote:

Hi,

I am having trouble understanding the avg_logFC results of an integrated dataset (control and condition) in Seurat (3.1) for the FindMarkers pipeline.

gene_name p_val avg_logFC pct.1 pct.2 p_val_adj

gene1 0 -0.270265934 1 0.115 0

gene2 0 -0.332681178 1 0.167 0

gene3 7.25E-119 0.251635681 0.855 0.238 1.45E-115

gene4 2.10E-86 0.255847237 0.856 0.293 4.19E-83

gene5 2.84E-76 0.257140547 0.923 0.399 5.68E-73

pct.1 represents control in cluster1 and pct.2 represents condition in cluster 1.

According to Seurat vignettes - avg_logFC : log fold-chage of the average expression between the two groups. Positive values indicate that the feature is more highly expressed in the first group

What about negative values? For gene 1, avg_logFC is -0.2. Does that mean gene 1 is downregulated in control group in cluster 1? But why is percentage of cells expressed in gene1 more in control cells than condition cells?

Am I missing something?

Thanks

sequencing rna-seq R • 689 views
ADD COMMENTlink modified 5 months ago • written 5 months ago by Payal100
0
gravatar for Payal
5 months ago by
Payal100
Payal100 wrote:

I also posted this query in Seurat Github issues page. Please follow the conversation here - https://github.com/satijalab/seurat/issues/3397

Summary:

first switch to RNA assay

DefaultAssay(objecti)  <- "RNA"
object_RNA <- NormalizeData(object, verbose = FALSE)

then, find markers for every cluster compared to all remaining cells, report only the positive ones

object_RNA.markers <- FindAllMarkers(object_RNA, only.pos = TRUE, min.pct = 0.25, logfc.threshold = 0.25)
ADD COMMENTlink modified 5 months ago • written 5 months ago by Payal100
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