Survival analysis with TCGA data in R | Create Kaplan-Meier Curves 

As someone who doesn't have a degree in Bioinformatics I am truly able to appreciate these things. Never stop making these videos!!

I'm going to do survival analysis tomorrow, and I found you updated this video, it's so so so helpful! You're my Godness😍😘

This is literally exactly the resource I was looking for several months ago. Glad to finally have it now. It's so nice to have example code and clear explanation.

Best channel for any bioinformatician ❤❤

Thank you very much for this very informative tutorial. Very helpful indeed.

You are the best! Thanks

Hi, I appreciate your work. Thanks for making these videos

Could you please make a video on integration of Chip-seq and RNA-seq data?

Thanks so much. This video is really useful. Besides, how can we prepare data to combine different factors to draw forest plot or to construct risk models? Could you please share this similar R code? Thanks again!

Greetings Miss Khusbu! Again a powerful video and it was really comprehensive. I have one question and will appreciate your guidance on it. If we perform survival analysis on an RNA-seq data from TCGA, and let’s say the expression matrix has 20K genes and 200 patients. After survival analysis I found 30 genes that has significant survival difference. So I want to pursue further and perform a multivariate cox regression of these 30 genes. Now my confusion is that what expression matrix we should use in multivariate cox model. Should we reduce initial expression matrix to only 30 genes as variables(columns) and 200 patients (as rows) or should we use the original expression matrix (having 20K genes and 200 patients and only put 30 genes in the cox equation : coxph(Surv(time, event) ~ gene1+ gene2 + gene3..+ gene 30 , data)). Will highly appreciate your comment on that. Thanks and keep doing the great work.

thanks. Could you please run a tut on combining Machine Learning in R and TCGA or cbioportal or Gdac or others? Thank you.

Thank you for your video! I just have question, why did you extracted the unstranded counts, but not any other count type?

If you ever write a book, let me know cause I'll pay 2000 euro to get it hands down!

Thank you so much for your amazing content. I just wanted to know how I could extract the TCGA counts for some non-coding regions specified in a bed file. Suggestions would be really helpful. Thanks!

Thank you very much for the excellent presentation. I am relatively new to TCGA-based R analysis. I was wondering if I can apply the same process to plot survival curves for a particular mutation using SNV data, such as the effect of BRCA1 mutation on the overall survival of ovarian cancer patients. Are there any significant changes that I need to make in the workflow to achieve this?

Thank you for this very helpful video. If I want to know correlation (pearson R-value) between some genes in TCGA-Breast Cancer , do I have to use fpkm_unstrand? Could you make video about this? Again, I really appreciate your effort!!

How do we change the number days upto which follow up is done? Say instead of 8000 days I want the data upto only 4000 days.

Have you ever heard or done MFA & mixOmics DIABLO analysis on TCGA data?

Hello mam, I am getting pvalue = 47.07. results are not significant. how to solve this. what could be the reason for this

risk.table is showing the followinf error: Error: 'yaml_body' is not an exported object from 'namespace:xfun'. can you please help

Can you please make video on top colleges of msc bioinformatics in India?

good

Hello didi .. I need to talk to you .. can you pls send ur contact details .. it's about my current project .. i have some questions based on bioinformatics

Dividing into groups is not good practice. Regression should be used. I did my whole thesis on this debate.

Why we usually chose “unstranded data” for analysis?? @bioinformagician @khushbu. Please do solve this query??