seurat findmarkers()

[Flu09]

hello, thank you for making this great tool. I cannot seem to understand how to use it.
I have differentially expressed genes from findmarkers() in seurat between diseased fibroblasts and control fibroblasts and MAST to account for latent variables.

The output has genes and the corresponding avg_log2fc and adj_pvalue. How to proceed because i have not found any tutorial to start from this point. I want to do Gene set enrichment or do you recommend me to prepare my data in a different way in order to be able to use this tool.

As I mentioned before I have celltype_disease and celltype_condition and looking forward to doing GSEA.

[chuiqin]

Thank you for using this tool. irGSEA aims to comprehensively score the results of multiple gene set scoring methods to help researchers quickly identify important and interesting gene sets. Unlike traditional GSEA, irGSEA scores individual cells and does not require the calculation of avg_log2fc or adj_pvalue in advance to obtain a gene ranking list. You can try running irGSEA through this example.

# load PBMC dataset by R package SeuratData
library(Seurat)
library(SeuratData)
# download 3k PBMCs from 10X Genomics
InstallData("pbmc3k")
data("pbmc3k.final")
pbmc3k.final <- SeuratObject::UpdateSeuratObject(pbmc3k.final)

# Seurat object
pbmc3k.final <- irGSEA.score(object = pbmc3k.final, assay = "RNA",
slot = "data", msigdb = T, species = "Homo sapiens",
category = "H", geneid = "symbol",
method = c("AUCell", "UCell", "singscore", "ssgsea"), kcdf = 'Gaussian')

# Integrated analysis
result.dge <- irGSEA.integrate(object = pbmc3k.final,
group.by = "seurat_annotations", metadata = NULL, col.name = NULL,
method = c("AUCell","UCell","singscore","ssgsea"))

irGSEA.heatmap.plot1 <- irGSEA.heatmap(object = result.dge, method = "RRA", top = 50, show.geneset = NULL)

irGSEA.heatmap.plot2 <- irGSEA.heatmap(object = result.dge, method = "ssgsea", top = 50, show.geneset = NULL)

geneset.show <- result.dge$RRA %>% dplyr::filter(pvalue <= 0.05) %>% dplyr::pull(Name) %>% unique(.)
irGSEA.heatmap.plot3 <- irGSEA.heatmap(object = result.dge, method = "RRA", show.geneset = geneset.show)

[Flu09]

@chuiqin thank you. do you think it is possible to use this tool to compare disease to healthy. I have a column named maincelltype.condition and group by this column or do I subset the object to have only diseased celltypes and then run irGSEA on diseased celltypes only? Thank you.

result.dge <- irGSEA.integrate(object = PD,
group.by = "maincelltype.condition", metadata =NULL, col.name = NULL,
method = c("AUCell","UCell","singscore","ssgsea"))
geneset.show <- result.dge$RRA %>% dplyr::filter(pvalue <= 0.05) %>% dplyr::pull(Name) %>% unique(.)
irGSEA.heatmap.plot <- irGSEA.heatmap(object = result.dge, method = "RRA", show.geneset = geneset.show)

[XjtuZhangKun-lab]

谢谢。您认为可以使用此工具将疾病与健康进行比较吗？我有一个名为 maincelltype.condition 的列并按此列进行分组，还是将对象子集设置为仅包含患病细胞类型，然后仅对患病细胞类型运行 irGSEA？谢谢。

result.dge <- irGSEA.integrate（object = PD， group.by = “maincelltype.condition”， metadata =NULL， col.name = NULL， method = c（“AUCell”，“UCell”，“singscore”，“ssgsea”）） geneset.show <- result.dge$RRA %>% dplyr：：filter（pvalue <= 0.05） %>% dplyr：:p ull（名称） %>% unique（.） irGSEA.heatmap.plot <- irGSEA.heatmap（object = result.dge， method = “RRA”， show.geneset = geneset.show）

May I ask, has this problem been solved?

[Flu09]

No I still wait for an answer. I hope they reply soon.