Tutorial: RNA-Seq Workflow with Galaxy | No Coding Involved (Step-by-Step)
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- Опубликовано: 20 авг 2020
- Today, I give a tutorial on an RNA-Seq workflow with the Galaxy webserver. No coding/programming involved.
My name is Arman Ghodsinia. I am taking a Masters in Radiation Biology in Oxford University. I have a BSc in Molecular Biology and Biotechnology.
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Hi thanks for watching! One minor point id like to make, after the initial stringtie step (9:40 - 11:20), you must then perform a 'stringtie merge step' before the second round of stringtie. For the stringtie merge step, use the stringtie output files as input and keep everything else as default. Finally, you must then perform another round of stringtie using the bam files as input and the stringtie merge file as reference (as shown from 12:09).
hi, did you use the GTF as a reference annotation to include in the merging?
@@goodvoucerry Yeah you have to or you wont get any gene ids just the 'mstrg'
In stringTie merge transcript which file will i use for Reference annotation to include in the merging?
The best RNA-Seq Workflow with Galaxy tutorial I have seen ever. Thank you so much ♥
This is such a great tutorial! I've been having some trouble using R for differential expression analysis and this was really helpful. Thanks for sharing!
Greetings from Mexico!
Very comprehensive tutorial. Simple to follow. Thanks.
This is the greatest video on RNA seq on the whole internet. Thank you from 💖
Perfect tutorial! Thanks Arman.
best tutorial ever. thank you so much. im a 9th grade student and i need this to complete my science fair. you are amazing !
Great tutorial! Thanks Arman!
That is awesome! Thank you so much!
thanks for this tutorial video. its was very helpful. although it took me a whole day to complete my analysis but i think it was because of my average internet speed. stay blessed.
Wow..great information...please upload more..thankyou very much for your knowledge that you shared
Thanks man! Just subscribed! I'm learning to use the Galaxy Webserver. 👍👍This makes it so much easier for me. Thank you
Glad I could help!
Very lucidly explained. Thanks
Great video... Keep us updated... Thanks alot...
Very helpful tutorial. Thank you.
Amazing. SOOO helpful
This is by far the most comprehensive, easy-to-follow walk through in using the Galaxy server. I personally use Trinity, but I want to try this since this does not make use of the command line. Cheers!
thank you :)
wow amazing video
Thank you Sir. Explained very clearly
Hi Arman, really a helpful video and so far nobody could explain RNA-seq analysis using galaxy the way you did. Just few requests if you can fulfill them that will be very helpful! Can you teach how to do heatmap, Volcano plot, KEGG analysis and GO analysis using galaxy?
great work, please upload more tutorials like that
I dont know what I did is a 100% correct, but I have gone much farther than I have ever been on Galaxy before and ended up with some results in fact. Thank you very much for this.
Great work Arman - Aditya from India
such helpful, Thank you !
You are super good. Thanks.
It was a wonderful tutorial Arman well explained. I would like to know the details of the input sequence with their accession number which will be very helpful for practice purpose
Nice tutorial !
Thank you so much
Very helpful tutorial. 👍👍👍 By far the best walkthrough I've seen. Does your workflow differ if you use a stranded library?
Thank you so much! The workflow is entirely the same. You just need to indicate that the library is stranded when prompted :)
hello sir its my humble request to you please upload more videos its very helpfull sir .
Very helpful and straight forward demonstration. How come other people made me so complicated until could not understand what they were doing at the end! By the way, in your stringtie step, you chose GTF/FGG3. Is this fix to choose for every RNA seq analysis including for mouse RNA seq too? I do not have bioinfo background, sorry for my Q. Thanks.
Great tutorial! Thank you so much! I just have a question, the final genelist with the protein upregulated or downregulated are from the treated cells o from the control cells? Thank you!
Hi Arman, thanks for sharing. Just have a quick question. Currently, I am using this pipeline: FASTQC > Trim Galore > HISAT2 > FeatureCounts > DESeq > GoSeq etc. Do you think there is any significant difference between these pipelines including the one you demonstrated here, which may affect the analysis results? If you had a chance to test and compare some tools available on Galaxy for RNA-seq analysis, I would like to hear which pipeline would be kind of the most reliable.
This tutorial was really helpful. Does DESeq2 require any minimum number of inputs for both conditions(control and treated)? I used one input for both conditions and it is not working.
I have been confused for a pretty long time analyzing my RNA seq data. But once I followed your video, things have been so smooth and all the doubts cleared. I want to refer this video in my manuscript. If this method has been been documented anywhere, please provide the reference.
One point: what will be the results if we select transcript counts instead of gene counts in DESeq2?
so useful, thank you! Have you ever processed bulk ATAC-seq as well?
I have a question, did you try STAR for alignment or bowtie2 and what is the best between them ?
how did you separated contolr and treated ?
What file is that - the one you uploaded
Hello Sir,
Very useful video 👍
How can I download raw RNA-Seq or normal tissue samples of an organism dataset from NCBI Or Ensembl? Can you please suggest to me?
Hi there!
Thank you for such informative video. Can we do the same analysis by assembling RNA seq data de novo ???
Hi, this is a very helpful video. How would I know from which type of data that I have is from? Is there a tool that can identify the type of genome? (This step will be in the in the "Download from web or upload from disk" window) Thanks
How to use DESeq2 on dataset from SRA database? it only has one dataset. for deseq we need atleast 2 for expression analysis? like u have treated and control, if i want to see interaction of pathogen how do I get the control dataset?
Hi,
I followed the pipeline and also did the string tie merged step between two string tie steps. Its gives me error in Deseq2 that :
Error in data.frame(..., check.names = FALSE) :
arguments imply differing number of rows: 16270, 14051, 16445, 14282
Calls: get_deseq_dataset ... eval -> eval -> eval -> cbind -> cbind -> data.frame
Can you help me?
In StringTie, i do not have a reference genome in GFF or GTF file
HELP
hi thanks for your helpful tutorial, i need help.
after running annotate deseq2 the column that is supposed to give the gene names is NA. can you please tell me why it's happening? I'm working with tomato sra files.
Please give detailed information about KEGG pathway analysis using Gprofiler
Hey really useful video! Any hints for a workflow for de novo RNA virus analysis with Galaxy. It will be sequenced with nanopore.
Thanks Arman, could you please link the sample data in the description? Otherwise, the tutorial is not possible to reproduce.
In my attempt, DESeq2 did not give any output. Any suggestions. Thanks. Helpful video though
hiaraman ,this is great, but is it possible for you to make another tuturial to process the raw rna seq data before uplodaing in galaxy.
Great tutorial! What is the format of the input files uploaded at 4:59?
For stringtie merge I don't believe the steps ,i.e. input data was shown at 11:29 timemark. So did you run the stringtie assembled transcripts with the reference annotation file as well, sir ?
Hi there was a stringtie merge step right after the first stringtie. then run the second round of stringtie using the stringtie merge file as the reference annotation. Thanks for pointing this out!
deseq annotate does not give gene names, it keeps it as NA. What to do? Thanks.
Instead of transcript IDs, I am getting MSTRG Ids. Is there any way to troubleshoot this issue?
i did not get any merge file when using string tie
is it an error
or i did some mistake uingthose
Do u have a tutorial video to analyse coding and non coding, and small RNA analysis. Thank U
how can ı download data? how did u download these datas, please help me?
Can you help me in understanding the file type you uploaded at the first place
Can you share any demo data....so that we could perform
Why do we need a second round of StringTie? Also what can I do if the number of lines for the gene count output for different groups are different? Thank you so much for your tutorial!
The first round is to quantify transcripts in each sample. Then you must perform a stringtie merge step to unify all the transcripts. And then finally, 1 last ro und of stringtie using the stringtie merge file as the reference annotation.
If you open Stringtie in galaxy, and scroll down to the description part of the page, there you will see ** Our recommended workflow includes the following steps ** ... you can check that out to better understand the workflow :)
Can you do microRNA seq analysis
Thanks for the tutorial, it is really good. I just want to ask that why did you change average read length to 50? How can I adjust that to my data?
Hi Tamer,
I believe its because for his sequencing the read length average was 50 whereas default set in Galaxy is 75 - if you have the ability to consult and choose, read length is a consideration behind initial experimental design.
If you are not sure your read length, just check the fastQC file for sequence length. It will tell you how long the read lengths are for your data, apply as relevant to your data.
Good luck!
Hi Arman, I followed your pipeline but for mouse RNA-seq but after the stringtie step, it show STRG.1xx for gene id instead of ENSMUSG0000001xx. Do you know how I should troubleshoot this?
Have you tried the 'annotate DESEQ2 output' tool after the DESEQ2 step?
DESeq2 is not working for me. Any suggestions?
Where is the data used, I want to try it
Hi, have any tutorial for epigenetic analysis in Galaxy, plz. send me the link. Thanks
Hi there,
After stringtie merge, the counts of gene hit comes as zero for all genes.
i know it's been 2 years but did you find the solution? i'm facing the same problem
How to download dataset😢
Hey Arman, it is a great video. Do you do data mining? If so, please can you do a tutorial about choosing the information that you've got! Thank your very much
Hi Stefania, what in particular do have in mind :) protein-protein interactions, gene ontology analysis?
@@armanghodsinia9946 I’m really lost about getting information of RNA-seq analysis for differential expression. I don’t know how to interpret the data. It’ll be awesome if you help me with that.
Nice day :)
I'll do my best to upload videos on interpreting RNA-seq results soon :)
hi Arman! I have a new question for you. I've upload my data reads and they're paired-end reads. When I apply trimmomatic on them, it gives me 3 outputs from each data: 1. R1 paired, 2. R2 paired, 3: R3 unpaired. In which one i should apply the next step that is HISAT2? I hope you're doing well. Also, when I annotate my genes in Annotate DESeq2 there's no name for them. All my genes are N/A in the gene name and it doesn't show to what chromosome they are in. Can you help me, please?
@@armanghodsinia9946 I had the same question. In addition, can you recommend a short workflow to merge paired end files? Each of my sample reads were run on two lanes to increase the number of counts so I have two R1 and 2 R2 reads for each paired end run sample. Great tutorial!
Can anyone help in bacterial transcriptome analysis please I need a helping hand
Hey Arman, thanks for the tutorial. While using DESeq2, I encountered the following error.
"Error in data.frame(..., check.names = FALSE) :
arguments imply differing number of rows: 5416, 5495
Calls: get_deseq_dataset ... eval -> eval -> eval -> cbind -> cbind -> data.frame".
How do I solve this?
Were you able to fix the problem?
@@disguisedgirl No, I couldn't.
Hi,
Did you figure out?
I have the same issue.
I followed the pipeline and also did the string tie merged step between two string tie steps. Its gives me error in Deseq2 that :
Error in data.frame(..., check.names = FALSE) :
arguments imply differing number of rows: 16270, 14051, 16445, 14282
Calls: get_deseq_dataset ... eval -> eval -> eval -> cbind -> cbind -> data.frame
Can you help me?
This is really a good tutorial.
is it a free webserver
Yes
Thanks for a great tutorial! I have quiet a few factors to compare so I've repeated DESeq2 and the annotation step a few times and every analysis returns N/A and no actual gene symbols. Not sure how to troubleshoot this. Is there another tool to convert the MSTRG gene IDs to gene symbols?
I am also facing the same problem. Have you found the solution ?
i'm having the same problem, can anyone help please?
Did anyone had the solution for this yet?
Thanks for the helpful tutorial. Even after performing DEseq annotation, the annotation is not working. The column has N/A at all positions. Do you have any suggestions for troubleshooting this?
okay, for those of you having the same problem...annotation worked good when I used feature counts instead of string tie for counting gene reads
@@poojamukherjee7615 how does FeatureCounts works?