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Hello Tommy, nice video!. I have a question about downloading RNAseq fastq files from SRA Run Selector using fastq-dl. For example, considering Accession ID GSE116951 (LibraryLayout: PAIRED-end) and Run SRR7511281, how can I get the two fastq files (foward and reverese) from the sample SRR7511281?

Thank you for the tutorial!

Point one is the life of all computational scientists 😂😂 even more so in the case of general IT techs

Thank you for valuable information. I am master graduated in zoology.i have no wet lab experience but i am interested in bioinformatics so that i am learning bioinformatics from scratch.this video gave me confidence.next 10year, i will become bioinformatics. scientist

I saw your handle on twitter and followed immediately. I am on this journey, to learn computational biology, bioinformatics, Cheminformatics from scratch and pivot in my career. I have a background in medical compliance and drug safety. I also work in the wet lab early. I missed doing research and I love science, so this is a good way to go back to my roots while learning the new technologies. I downloaded your 6 steps guide! I am excited!

Thank you very much! This was a very rich and personal podcast on RUclips! I have been having doubts and confusion to where to start bioinformatics and how to change from biotechnology to bioinformatics career. I think i have found the right channel for me!!❤

I have followed your videos along with videos from "Bioinformagician" since very long. I am an international graduate student of Bioinformatics in US(will be graduated in December 2024) with my undergraduate degree in health science. Could you please make video about how students like me should approach to find a job in bioinformatics, currently i am working as a data analytics intern at a pharmaceutical manufacturing. I have some academic research experience in single cell and multi omics and currently looking for internship in bioinformatics or full time position. Thank you in advance!

Can you please make a video to analyse data using Anaconda?

Thank you for another excellent and informative videos! I think the audio volume of your video is relatively lower than others

The only one I would eat grilled dog with

The following commond is not executable "csvtk pretty -t GSE197576_raw_gene_counts_matrix.tsv.gz | less -S" When I tried to execute it in the terminal, it says "-bash: csvtk: command not found". Even after "pip install csvkit", I still recieve the same error message. Could you please guide me how to make it work?

Thank you so much!!

Thank you for this tutorial! Before, the only way I knew how to get the NCBI GEO metadata was to download the series matrix file but that formatting is awful.

Hi Dr. Ming! I found this video super helpful, but I have one quick question. I am working with this dataset: www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE123139. After downloading RAW.tar, I can only txt.gz files; I do not see any anno.txt.gz. I am wondering if you have any suggestions on how I can create the seurat file. Do I need to find the metadata somewhere else? Thank you so much!!

Thanks for this useful video! One question - I have, let's say 4 GSEA's to do for 4 DESeq2 results (4 different DESeq2 comparisons; 4 treatments compared to the same control), how can I visualize them "all together" in a dotplot or barplot to investigate the GO terms that they have in common/different? Thank you!

"How easy is it to install?" This is SO true. I've not used tools that may have been great because installing them was nearly impossible. Then there's "does it actually work?" which is... not always true. I've contemplated including that in the "why" of methods sections... why did I choose this package? Because it's the most appropriate one I could get to run.

"here" package is very useful! thank you

I can't believe I've only just found such an informative video! It's really helpful. Thank you so much for sharing your knowledge.

This is very helpful. Thanks, Tommy

thanks for great video

Thx

Thanks, great resources.

If I understand correctly, you can basically use RFs to cluster data in a way that relates to an outcome variable? Like, if you wanted to group patients by demographic features, height, weight, etc. in such a way that group membership can reasonably accurately predict treatment outcomes, you could build an RF with the treatment outcome as the dependent variable, then use the proximity matrix to run a clustering algorithm? If so, thats SUUUUPER useful!!!

Hi, brilliant video, can this same method be used to cluster a dataset with only categorical values?

Thanks Tommy, your channel is really helpfull. I have a question though. I have just got my neuroscience degree and want to get into bioinformatics, i dont want to do a masters, would doing online courses like python, statstics and projects be sufficient to land a job?

Hi Tommy, Thanks for the great resources. Would you recommend books over online courses on Coursera and Udemy? What is your advice for someone lacking math skills who wants to go into bioinformatics? What are some of the must-have skills to land a job in bioinformatics? Thanks.

Thank you Dr. Tommy! Amazing collection! Are there any books you would suggest related to Machine Learning for Omics or biology in general?

Hello, the tutorial was very informative and i am really thankful for this wonderful video. I am little bit confused. please let me know if we have multiple samples like given in this video then (1) we will first create the seurat object for each sample and then we will merge all these seurat object into one big seurat object before going into quality control, normalization, clustering and UMAP (2) or no, we will first create a seurat object for each samples and then we will perform a quality control, normalization, clustering, and UMAP onto this seurat object. and we will perform the same process for all othe seurat object of other samples and at the end we will merge the seurat? which one is correct (1) or (2)? looking forward to hearing from you soon

Thanks Tommy ! Can you give some tips on how to manage self learning Those are complex topics for biologists and dense textbooks. Do you recommend following small chuncks schedule? Dedicating a month only for ‏‪it ? Etc

Thx for the great list of books, I will definitely get some of them. Do you maybe also have any recommendations for proteomics & metabolomics ?

I tried this pipeline but with h5 files and I'm stuck. Do you have a tutorial for that? Please and thank you.

Thank you so much. 11:30 was exactly what I needed.

Thank you Dr. Ming Tommy Tang.

Sir, I don’t have knowledge of R programming or any other computer language. But I want to GSEA analysis of my rna seq data. Can you suggest any methods

Thank you very much! The video is very useful but I am still struggling with merging and splitting assays in Seurat. It would be cool if you could make a video about that :)

Cool!

Sir I want to know if you are familiar with circular rna analysis

Sir is this book still there i want to purchase it

The RAM: 💀

Can you guide on how to make pipeline for tumor-only samples?

Thanks! The files I've downloaded from GEO are in .CEL.gz and .CHP.gz format - how can I use these with your work flow?

Totally useful, thanks for sharing this. I would love to see some videos on regular expressions (so we can wrangle everything easier) and awk!

This video is exactly what I am looking for.

Thank you so much for informative video ❤. I'm a PhD student from china. I recently found your channel, I am a beginner or r learner. I want to learn TCGA or geo data wrangling, I mean mostly use it only cancer vs normal, I want to see how much we have options in dataset to make group. If you have any video please recommend me, or I also can arrange a online class if you have any appointment.

Thank you for great video!!

That's an amazing lecture!

Thank you for the video. Can you fix the resolution? The video is too blurry.

Thank you for the resources!!! Excited to go over them :D

Some distracting static noise or loud mouse clicking in this video. I love this channel, just a heads up!

thank you for these instructions could you please make a video teaching aspiring phd condidates how to look for research subjects (what to read/ how to spot ideas for research/ the reasoning etc ) thank u