Entering edit mode
2.7 years ago
mshubham
•
0
Hi All, I have performed Seurat-based differential expression. (FindMarkers()) on my current dataset to find out differentially expressed genes in treated conditions as compared to control. What tool in R can be used to generate or annotated the pathways associated with the genes afterward? I tried using pathfindR but seems not so useful in marking the pathways.
Please do let me know. This will help me in further analyzing my data.
I'm partial to clusterProfiler since it integrates well with a few databases, such as the reactome pathway database and KEGG.
I'm trying to use clusterProfiler but am not able to understand the creation of KEGG data input as mentioned here. Data frame after seurat Findmarkers() gives rownames as gene names. Can I use them directly in clusterProfiler or need to convert them? If you have better tutorial for the same, please do share. Also, which function to use here; gseKEGG() or enrichKEGG?
You need to use the bitr function to change your gene names into one of the supported input types, such as kegg ID, NCBI gene ID, or uniprot. The official clusterprofiler vignette is pretty extensive, I recommend giving it a read.
I converted my Ensemble Gene names to ENREZID and tried to perform enrichKEGG, but I am getting an error saying no genes can be mapped.
Reading KEGG annotation online:
Reading KEGG annotation online:
--> No gene can be mapped.... --> Expected input gene ID: 18642,72157,18640,76051,54397,66681 --> return NULL...
I tried bitr_kegg function to check the gene IDs and it says ~94% of genes does not map.
Warning message: In bitr_kegg(names(Kegg_gene_list), fromType = "ncbi-geneid", toType = "Module", : 94.09% of input gene IDs are fail to map...
After Seurat Findmarkers(), if I need to annotate the pathways of gene, do I even need to use enrichKEGG, if Yes, then what is wrong here. Please do help.