@miguelreis6249
Laura, thank you so much for doing these. Even hard heads like me can follow our tutorials, amazing stuff! The world bows in amazement.
@xlxeat
The tutorial is very helpful even i ran the enrichment pipeline lots of times before. Your code gave me useful tips!
@pulcinella96
Laura, thank you so much for all of your amazing content. It's helped me so much during my MSc course. Just wanted you to know that all of your hard work is much appreciated!
@xiaofeili7379
This is a great tutorial. I have a question, how about if I want to analyze mouse data and GSEA didn't have a murine KEGG gene set?
@joeyoviedo5202
wow, so glad I found your channel, very high quality content. I would love to see more workflows using other clusterProfiler functions. Also, It would be cool to have workflow options for generating data visualizations that are good for comparing exposure groups and exposure windows using overlapping significant DEGs. Thank you! Have a squidtastic🦑day!
@苏秋羊
I need help, teacher. Since df include all the gene not just the differential genes, how to get the whole genes list since i saw that some p value is above 0.05, how do i get that list for my scRNA analysis. Appreciate it.
@shawsheryl5092
Aaaaaaaaawesome!!!!! I've finished watching all your videos about pathway analysis and they really help a lot!! I'm really grateful for your excellent explaination!!!! But I wonder if I could apply GSEA into proteomic analysis? I've get the expression matrix of the proteins, but I don't know if I could match the protein ids with the gene set... could you please provide me some suggestions? I'd be approciate it a lot!!
@markrenton6981
Has anyone tried changing all of the mouse .gmt files to .RDS? I can get all of them to do it except for the GO CC set. Anyone else run into this problem? It will read the .gmt file, but when i execute the saveRDS() function, it just doesn't appear in the folder like it did for all of the other .gmt files
@aidaht1
your channel and videos are greatI liked your website as well, ! thanks so much for your help. I have a question, I have conducted differential expression analysis on TCGA-PRAD and a microarray dataset (GPL570) to get differential expressed genes between Normal and Cancer tissues. after that I drew a Venn diagram to get common DEGs between these two dataset, however my common DEGs ar just gene symbols, I don't have logFC or p.value for them(I have these for each of the datasets but I don't have them after drawing Venn diagram). how can I do PEA with cluster pofiler for my common DEGs obtained from Venn diagram? thanks in advance.
@LeviRafal
Should codes in this chunk: # Subset to those pathways that have p adj < cutoff and gene count > cutoff (you can also do this in the enricher function) target_pws <- unique(res_df$ID[res_df$p.adjust < padj_cutoff & res_df$Count > genecount_cutoff]) # select only target pathways have p adjusted < 0.05 and at least 6 genes res_df <- res_df[res_df$ID %in% target_pws, ] be corrected to: res_df <- res_df %>% filter(p.adjust < padj_cutoff & res_df$Count > genecount_cutoff) as there are some cases when one of the two direction (up or down) of pathways with the same name does not pass the padj_cutoff, so directly filtering the values themselves would be more accurate?
@KeshavSharma-lh7zf
can i follow the same for proteomics data
@Myri912
Hello! thank you very much for the video, it has helped me a lot. However I had a query as I have played the whole script on my computer with my own SDR data. I have run the whole script and everything seems to be correct except when I run the last step "target_pws <- unique(res_df$ID[res_df$p.adjust < padj_cutoff])" and "res_df <- res_df[res_df$ID %in% target_pws, ]" which reduces the list to a single gene. I have looked at the default values of the function and they are not exaggerated, but what would you recommend me to do to have a larger list? Thanks in advance!
@praveenkhatri4084
Very informative, I was wondering, If I want to GSEA for plant for eg soybean, how I do that, as ORG.db library is not available for that, can u plz help me with that
@shrivastava3892
The differential data that you loaded in the r script initially, which has approx 30 thousand something genes and four variables, are they pre-processed data, like removing the duplicates and adjusting the p values and log FC?? Or are they raw data tT saved from r script?
@MinuMathews-dc3oy
When i put in df <- read.csv(paste0(in_path, 'severevshealthy_degresults.csv'), row.names = 1), why am i getting the error Error in file(file, "rt") : cannot open the connection In addition: Warning message: In file(file, "rt") : cannot open file 'Datasets/severevshealthy_degresults.csv': No such file or directory.
@mihacerne7313
SQUUUUUUUUUUUUIDTAAAAAAASTICCCCCC
@tanmoychatterjee7922
Please ma'am don't use preinputed code it is not helpful. We need how to write R script
@nidhilangelomariyelil6091
Lady you are good. But you only tell the facts half only. We get easily confused in certain points like gmt files in half way. If are decided to teach just do it correctly. For beginners in bioinformatics you are mocking is. Half truth is worse and worst than lying.
@singh_nimisha