you are just amazing. I always felt afraid from R and RNA-seq analysis, but you made it super clear for me. Thanks!
@coolalexpcs6 ай бұрын
It's a really fantastic lecture teaching ggplot specifically for gene expression data! Really helpful!
@usmanasghar11274 күн бұрын
You are doing really amazing work keep it up.
@lavanyakakimallaiah2 жыл бұрын
I was finding it difficult to understand from online resources.... your video about gene expression really superb...I was able to understand all the things Thanks for the video
@tulikabhardwaj4842 жыл бұрын
I am so much addicted to your videos. Please kindly made some videos on metatranscriptomics
@Bioinformagician2 жыл бұрын
Thank you, I will surely think about making a video on it :)
@tulikabhardwaj4842 жыл бұрын
@@Bioinformagician then surely, I am eagerly waiting for that day. Good luck to you girl.😀
@Bioinformagician2 жыл бұрын
@@tulikabhardwaj484 Thank you! 😃
@setarehsohail54222 жыл бұрын
Unbelievable! you are genius! How do you teach these complex issues so easy and understandable?! Thanks from bottom of heart!
@Bioinformagician2 жыл бұрын
I really appreciate your kind words. Thank you very much :)
@kimiaslk9348 Жыл бұрын
your videos really help me through my masters, you are so smart and inspiring ! thank you
@lincysubi6735Ай бұрын
Excellent explanation...
@nikitamaurya45182 ай бұрын
Thank you so much!
@jowrow76652 жыл бұрын
Thanks sister. You are just doing nothing but a great job. I wish you all the best.
@sanjaisrao4842 жыл бұрын
Exellent explaination Thank you very much Keep uploading 🥰
@o1kun Жыл бұрын
These videos are really really helpful! You really saved my research 🎉
@shrishteekandoi1202 жыл бұрын
Fabulous Explanation ! I love how you make things so much easier to understand !
@nagavenicavuturu91795 ай бұрын
Yes your explanation is really great
@bzaruk2 жыл бұрын
All your content is PRICELESS - thank you so much! :)
@gaellelelandais2624 Жыл бұрын
Very nice ! Thank you, you're doing a great job, very useful for other teachers (as I am). Thank you.
@giulianacoatti8163 Жыл бұрын
I simply LOVE YOUR CHANEL!!! THANK YOU SO MUCH FOR SHARING!!!
@vahidgorganli8895 Жыл бұрын
Great😀
@luischipres283 Жыл бұрын
¡Gracias!
@RicardoRiveroHerrera2 жыл бұрын
Really good content! Keep it up!
@Bioinformagician2 жыл бұрын
Thank you! :)
@parthibanm75611 ай бұрын
Can u please put lectures on comparative metabolomics data analysis, you have been amazing
@tushardhyani39312 жыл бұрын
Thank you for this video !!
@umarsheikh19922 жыл бұрын
Hie, Thank you the helpful tutorial for understanding and analyzing the gene expression data sets. As u have started the videos series beginning from how to download the data set to visualisation. Could you please add a video where in you can show how to perform differential gene expression with edgeR, limma, and DESeq2 of the same data set. We now we have the data in the dat. Long format, could we explore the differentially expressing gene between tumor and normal sample and plot the data using heatmap. Regards
@Bioinformagician2 жыл бұрын
That's a great suggestion. I'll surely plan on making a video in continuation with this dataset and performing downstream analysis.
@neetimittal9189 Жыл бұрын
Hi Could you please make a tutorial on workflow for processing, qc and analysis of a DNA methylation data on Illumina 450K or EPIC platforms? Your videos are really helpful!
@sciencetutor_businessguy Жыл бұрын
i think the data set you used is different from the one downloaded as there was no gene BRCA1 AND BRCA2 in the genes in the dataset. While i filtered , it showed no result with the filtering using both gene names. Does anyone face the same challenge?
@vijethavk8 ай бұрын
For the heatmaps, can the sample names be made perpendicular to the columns and therefore more readable?
@yahyayozbatiran Жыл бұрын
Hello, how can i plot a specific gene expression in cancer subtypes from tcga, for example; I want to plot> MSH2 gene expressions in Colon Mucinous versus Colon Adenocarcinoma
@user-uq3qh2cy9v Жыл бұрын
in this sample, you used "fill=tissue", then bars of different tissue colors are grouped together. However, if you change it into "fill=metastasis", like below coded, then the bars of different colors are mingled. Is there any way we can group it again? dat.long %>% filter(gene=='BRAC1') %>% ggplot(., aes(x=sample, y=FPKM, fill=metastasis)) + geom_col()
@manuelsokolov Жыл бұрын
This video was very helpfull! If I may ask can you compare like this across samples having the data normalized in FPKM?
@zulfakhan2655 Жыл бұрын
can you please explain how can we generate Differentially expressed gene via this type of data... that is gene expression data.
@dharmeshbisoriya7728 Жыл бұрын
Can we use the FPKM values directly to compare between samples.?
@shreymehta4973 Жыл бұрын
Hi! Quick question -- is it possible to use other values besides FPKM for comparison? What other types of normalized values do you recommend using for all these plots? Thank you!
@nagavenicavuturu91795 ай бұрын
Does the software s mentioned will be available at free of cost???
@karthibiotech4262 жыл бұрын
i want to know about the file of your input GSE183947_long format.txt...is this the previous .CSV file you used...?
@Bioinformagician2 жыл бұрын
It is the CSV file associated with the record GSE183947, just manipulated the shape of the data from wide to long and saved it as GSE183947_long format.txt.
@ashutoshs1966 Жыл бұрын
Can these things be done in Studio as well
@ducphucngo3938 Жыл бұрын
Is this method still available for microarray data? Thanks in advance
@user-no1jk9km7r Жыл бұрын
i love you
@user-ft5bh9yr1j2 жыл бұрын
Hey, great tutorial! Just a note that you do a lot of "uhhhh/ahh" while you talk, it's a little distracting hahaha
@Bioinformagician2 жыл бұрын
I am happy you find the tutorial great inspite of uhh ahh :P But in all good spirit point noted, thanks for bringing that to my notice :)