Just leaving a comment hopefully for people that are trying to use it recently. The Expression Dataset File by default is no longer like that: just remove the first 2 rows (starting with the row: Name "tab" Description "tab" ...) I did that and everything run smoothly! You can also see it as the last example in the user guide web page (did they change the default standard?)
Hi Magaraju-India, heatmaps are included in the outputs, but they don't show all the genes. This is a better tool if you just want heatmaps: www.heatmapper.ca/
@@GenomicsGurus Madam, I would like to have an output represented at 32min:49 sec to 33min.30 sec of your video. Please let me know the process with options. Thank you.
Hi, you don't have to select any options -the heat maps appear automatically underneath the first table. However, sometimes they don't display as it depends on the html file being able to access the image file eg I had trouble when I saved the output to an online location (one drive) and this was solved when I saved the outputs to my c drive. If they still don't load up, the heat maps are saved as individual pictures in the folder where you save the output, so go to your file manager, find the folder, and view them from there.
Thank you for this helpful tutorial! I like how you explained all the output metrics in detail. I had zero encounters with RNA seq data analysis and within a few hours, I managed to compare my gene sets of interest in my experimental groups.
I have a note about what you said at 3:33 The genes are ranked based on their P. Value and fold change, so saying based on counts isn't entirely true. Thank you so much for the video it's really helpful.
Thank you Dr. West! Good job, great tutorial. I even liked your warm voice and your accent... it sounds like you are American, but maybe it is the Scottish accent... I've never been in Scotland, I couldn't say.
I'm glad you found the tutorial useful! I think my accent is mainly Scottish, but there's probably a twinge of the eastern USA and north west England as well ;)
Thank you, was helpful to understand and perform GSEA. I would like you to cover network construction between miRNA-mRNA expression profiles using Cytoscape
There is a mistake in the explanation. Do not add the #1.2 plus number of genes and columns in the file when saving as TXT, it only works when using GCT.
@@GenomicsGurus Thank you, it would be great to see the integrative analysis of RNA-Seq and Chip-Seq. EaSeq would be a good option for such a analysis but unfortunately I am not an expert in bioinformatics field.
Hi Katherine...........excellent explanation of GSEA for beginners.......... Can you please cover using ClueGo plugin in Cytoscape for building PPI maps..........
I need to add one important point here is that the file format of the expression data mentioned here should have a .gct extension. It shouldn't be a .txt extension. tab-delimited file doesn't take the the two rows at the top
@@GenomicsGurus Dear Madam, Can we change color of the heat maps. It is all blue and red whilst I run GSEA and check the output folder. Is it possible. Please let me know madam. Thank you.
@@scienceforus8669 There is an option in the advanced settings to save the heatmap data as a gct file. You could then import that into a web tool for heatmaps where you can customise the colours.
This video is really helpful. I learned a lot from it. I was wondering do you have an example for time series analysis. Since the GSEA website doesn't talk too much about it, I have no idea to start the time series analysis.
I'm doing my RNA Seq data analysis, and I've got the differentially expressed genes in an excel sheet. I would like to do pathway analysis to see which pathways are differentially regulated now. I don't know how to do that, I hope this tutorial helps me! Thanks!
Glad you found it useful. I'm not sure when I'll get the time to do one on pre-ranked GSEA. Is that something you want to try? There's only a couple of things that are different, I think - I can write them down for you.
@@sumitpaliwal1540 This is the link describing the rnk format your file needs to be in: software.broadinstitute.org/cancer/software/gsea/wiki/index.php/Data_formats#RNK:_Ranked_list_file_format_.28.2A.rnk.29 This method doesn't tolerate duplicate gene names in your list, though, which is a problem when I use Ensemble IDs, as each gene may have several different Ensemble gene IDs. If you are using Ensemble IDs I suggest you convert to gene symbols first, then sort by name (in excel) to identify any duplicates which you can then remove. If you're still having trouble, email me: katherine.west at glasgow.ac.uk and I'll have a look at your file
@@GenomicsGurus I do not have any duplicates in the list. The error I get is "After pruning, none of the gene sets passed size threshold". I can send you the screenshot and the file.
Hello, It is really a great video. I have a question related to validation of repurposed drugs using GSEA. Actually, I am a beginner and want to do this. Can you please guide me how can I validate the drugs that I have using GSEA? Looking forward for your response
Firstly, thank you for the tutorial, I have found it really helpful. I have a question regarding to what can be concluded from the enrichment. I have performed a preranked method and the results showed an enrichment in the pathway, however one of the genes that is highly expressed has an inhibitory function in the pathway. So my question is if the ES shows only the enrichment of the genes (either activators or inhibitors) or also the directionality of the pathway. Thank you in advance.
Think it only tells you about the pathway in general and not on the individual genes in the pathway. In case you want to know about the directionality for individual genes, probably you would have to check your individual genes and the fold change for that gene from your DE table.
Amazing tutorial. My question is, if i have RNA-seq results giving different expressed genes for different cell lines and I want to compare in order to check for example which cell line expresses genes (significant upregulated enrichment) associated with angiogenesis. In this case, in my expression dataset file, the first column would include ENS id's for these genes, but I have sometimes completely different genes in different cell lines (with 3 samples per cell line), so what is the appropriate way to organize this data?
Great video! Thanks a lot for the explanation. I was wondering if you know how to use a continuous phenotype label for a time course actually. I tried following the user guide for that but I couldn't really do it. Thanks :)
I've not tried it myself, but it doesn't look too complicated. There are lots of ways to make mistakes with these input files, though, as my students will testify! If you want to email your files to me, I can have a look at them.....katherine.west at glasgow.ac.uk
Thank you for this video I have a problem: GSEA don't run with download files from GSEA with .gmt format. I want to use the gene sets that I selected. Can anybody help me? Thank you so much
Hi Dr. West, great tutorial. I have one question looking for your help. When creating Phenotype labels file in excel, you mentioned to save as tab-delimited text file with the extension.cls. How to do this? Excel does not have an option to save a file as cls file. Thanks.
This content is a treasure. Thank you so much Dr. West. Just in case someone reads my comment: I have doubts about which values I need to put in the Expression data set file (10:37). I just have two groups and I have the "Raw comparison" values and other corrected values such as reads per kilobase per million (RPKM) and Transcripts Per Kilobase Million (TPM). Which one should I use? Another question: My data comes from a RNA-seq analysis of Mus musculus cells. Which Chip platform (23:40) should I choose? Many thanks! : )
Hi Joan, sorry for the slow reply. TPM is probably the best dataset to use. Your genes are probably named as ensemble gene IDs (ENSMUSGXxxx) so "mouse ensembl gene ID human orthologs" with the latest number would be the right chip platform to use.
You shouldn't need the gene ID - choose a gene symbol chip platform instead of a gene ID chip platform when running GSEA. The long answer to your question is that you can download a file from ensembl that lists gene ID and gene symbols, and you can use vlookup in excel to look up IDs for known gene symbols and vice versa.
