Hi! I know you get this a lot but thank you so much for these turorials! I recently just got into sc RNA sequencing and using seurat, and your channel has been a godsend.
Would sc-type (cell annotation package) be a interesting alternative to singleR? I mean, what do you think about sc-type? Thank you for this excelent tutorial !!
Hi, great tutorial, thank you! I have an error when I try to load the reference data by celldex. (Error in `collect()`: ! Failed to collect lazy table. Caused by error in `db_collect()`: ! Arguments in `...` must be used. ✖ Problematic argument: • ..1 = Inf ℹ Did you misspell an argument name? Run `rlang::last_trace()` to see where the error occurred.) Do you happen to know how to fix this? People online have suggested downgrading the dplyr package but that causes problems with Seurat, at least for me. Thanks!
Thanks for sharing this is reallt helpful. I wonder if you could do step by step for MuSic2 deconvolution of bulk-RNAseq using single cell data set, Cheers
Hello! I had a quick question about the last heat map- can you explain again what the scale on the blue and white heatmap actually means? What is "3" referring to in the heatmap? What is "1"? I understand that the dark blue means that there are more of that cell type in the cluster and white means none, but I can't explain where the number on the color scale is actually coming from. Thank you so much for your videos, they have helped me so much as I learn scRNAseq!
Hello, this is great! Thank you. I did some of these on individual dataset. Could this SingleR be applied to the integrated dataset? Basically, I have 4 timepoints data GEX, to compare them, I generated an integrated dataset and do the umap analysis. I tryied to apply the SingleR analysis on this UMAP, but failed. Is the integrated data not suitable for this? Thank you.
Hi, the video was really helpful. But are there any reference dataset packages like 'celldex' in order to use information from drosophila as a reference dataset.
Hello..!! I want to say that these tutorial videos has been really helpful for me but I had one query. When we run the code of find clusters, for instance, in this tutorial video you seem to have got 0 to 24 clusters but when we group by the single R labels in a dimplot, it seems to generate only 12 clusters in the dimplot. Why is that so?
I transformed with logcount a reference dataabse (lu et al 2023), but for my test data, do you recommend us to work on fully integrated datast (with SCT and the most variable features) or with not transformed dataset ?
Hi! Do you have any recommendations for automatic annotation methods that would incorporate both RNA and cell surface marker data (i.e. for a CITE-seq dataste)?
Please make a video on asap University genome browser and how to analyse genomic data and make graphs & charts for beginners. It will be very helpful for college students.
I watched the videos on both microarray and bulk RNA-seq data analysis methods. I was wondering if there are any approaches available for integrating samples obtained from both platforms for analysis.
Hi! I know you get this a lot but thank you so much for these turorials! I recently just got into sc RNA sequencing and using seurat, and your channel has been a godsend.
The videos uploaded on the channel have been very helpful! many thanks
Thank you so much for sharing all the useful bioinformatic knowledge!!
Would sc-type (cell annotation package) be a interesting alternative to singleR? I mean, what do you think about sc-type?
Thank you for this excelent tutorial !!
Hi, great tutorial, thank you! I have an error when I try to load the reference data by celldex.
(Error in `collect()`:
! Failed to collect lazy table.
Caused by error in `db_collect()`:
! Arguments in `...` must be used.
✖ Problematic argument:
• ..1 = Inf
ℹ Did you misspell an argument name?
Run `rlang::last_trace()` to see where the error occurred.)
Do you happen to know how to fix this? People online have suggested downgrading the dplyr package but that causes problems with Seurat, at least for me.
Thanks!
Thanks for sharing this is reallt helpful. I wonder if you could do step by step for MuSic2 deconvolution of bulk-RNAseq using single cell data set, Cheers
Great tutorial
Thank you!
Hello! I had a quick question about the last heat map- can you explain again what the scale on the blue and white heatmap actually means? What is "3" referring to in the heatmap? What is "1"? I understand that the dark blue means that there are more of that cell type in the cluster and white means none, but I can't explain where the number on the color scale is actually coming from. Thank you so much for your videos, they have helped me so much as I learn scRNAseq!
Hello, this is great! Thank you. I did some of these on individual dataset. Could this SingleR be applied to the integrated dataset? Basically, I have 4 timepoints data GEX, to compare them, I generated an integrated dataset and do the umap analysis. I tryied to apply the SingleR analysis on this UMAP, but failed. Is the integrated data not suitable for this? Thank you.
Hi, the video was really helpful. But are there any reference dataset packages like 'celldex' in order to use information from drosophila as a reference dataset.
Hello..!! I want to say that these tutorial videos has been really helpful for me but I had one query. When we run the code of find clusters, for instance, in this tutorial video you seem to have got 0 to 24 clusters but when we group by the single R labels in a dimplot, it seems to generate only 12 clusters in the dimplot. Why is that so?
I transformed with logcount a reference dataabse (lu et al 2023), but for my test data, do you recommend us to work on fully integrated datast (with SCT and the most variable features) or with not transformed dataset ?
very helpful.. thank you 😀 but I have one query, which reference dataset should be used if you have stem cell differentiation data ?
Hi! Do you have any recommendations for automatic annotation methods that would incorporate both RNA and cell surface marker data (i.e. for a CITE-seq dataste)?
did you figure this out?
Please make a video on asap University genome browser and how to analyse genomic data and make graphs & charts for beginners. It will be very helpful for college students.
I watched the videos on both microarray and bulk RNA-seq data analysis methods. I was wondering if there are any approaches available for integrating samples obtained from both platforms for analysis.
could you do a tutorial for the software tool pRESTO (from Immcantation) please? I'm learning a lot with all your videos, thank you so much!
nice
I was unable to install celldex
Well