Comparing scRNA-Seq | Suerat Integration Analysis (Brief)

It is often that we need to combined the datasets from two separate condition with very different sequencing pipeline and output. They might also contain very different results and sensitivity.
Ultimately, the details in experimental design is going to another book of content, so assuming the experimental setup for the two samples is correct and comparable, how can you integrate the two datasets and compare the gene expression between them?
Script used in this video
github.com/brandonyph/Seurat_...
original website
satijalab.org/seurat/articles...
Email: [e-mail]
Website: www.liquidbrain.org/videos
Patreon: / liquidbrain

[@pingliu1310]

Thanks a lot for your video, quite a nice introduction!!!!

[@kitdordkhar4964]

Useful for my analysis. Thanks LB 🙂

[@paroletatel]

Thank you

[@mahamoussa5712]

You are a fabulous teacher, of cures! Could you post your other video?

[@RituVerma27]

Hello Brandon, I am having the following error - Error in which(x = object.classes, useNames = TRUE) :
argument to 'which' is not logical
in the step where we are trying to find anchors (chapter 1)

[@dannieqing535]

Hi Brandon, do you know how to get gene with logFC with different treatment. It is easy to make dot plot, but how to get those sample level dataset and read in csv file?Thanks!

[@mamiburgac2032]

Hello, first of all thank you for explaining the Satijilab code! Its is really great what you are doing!
However, I have a very short question. On my analysis there are more than 2 samples, therefore
sample_detect

[@MohammadSaleem-vl8sn]

Please make tutorial on how we can use machine learning like random forest, bortula , k means , in GWAS, disease prediction,

[@paapangromearound446]

Hi, Thank you very much for many of your vdo. That's brilliant helpful for me.
I have a question is that, I did a single cell sequencing. However, I found out that there is the batch effect in my dataset.
My question is that When I look at the data I feel like the batch 1 usually can read with the lower count number while batch 2 shown much more different in the scale. and this will cause the problem because I cannot compare this control and treatment by pooling the data together because both of them are in different scale.
In this case which method would be the best fit to try and does quantile normalization is necessary.

[@LiquidBrain]

Hi you may regress out the batch effect at the step “scaleData”, with the function vars.to.regress = “your_sample_batch_ID”
Hope this helps - Lind

[@paapangromearound446]

@@LiquidBrain thank you so much, I would like to ask if you are open for some collaboration in research?

[@LiquidBrain]

@@paapangromearound446 Oh ya sure, you can drop us an email here [e-mail]

[@paapangromearound446]

@@LiquidBrain Thank you very much, I have sent you my email. :)

[@paapangromearound446]

@@LiquidBrain Hi, I am sorry for my delay response of my email due to my health circumstance. However, I have sent you the information. I am very sorry for my late reply again. I am looking forward for our discussion. Thank you very much

[@chih-hanh.9514]

Hi, thank you for your video. I have an error message when I was in this line "merged.WIHN

[@chih-hanh.9514]

For those who have the same problem, I solved this issue by downgrading Seurat from v5 to v4.3.0.