Thank you so much for posting this. Hope to see more of cellranger

could not read H5, need to install hdf5r, how to solve this problems

Hello and respect Special thanks for your useful videos I have an important question. I would appreciate it if you could help me I have performed spatial transcriptome data analysis (Visium HD) for colorectal cancer as instructed in your videos If we analyze the spatial transcriptomics data and want to continue the QuPath analysis, how should we find the file related to the QuPath software that is related to colorectal cancer? And related to the results of our analysis? I mean, how can we find the qptiff file that you upload in QuPath software for colorectal cancer? With great respect

I dont have Library(tidyverse), Any suggestion?

Is this a pipeline for Xenium data alone, or includes the single-cell RNA data in it ?

I have one more doubt, if we are using only one sample, then can we use fgsea, is it make any sense.

How can I analyse single .tsv file on R using Seurat? e.g. GEO - GSE249493

library(Seurat) library(spacexr) library(tidyverse) set.seed(12345) ### Load Visium HD data cortex <- Load10X_Spatial(data.dir = "../Seurat/Visium_HD/", bin.size = 8) # bin.size = C(2,8,16) cortex <- NormalizeData(cortex) cortex <- FindVariableFeatures(cortex) cortex <- ScaleData(cortex) # sketch the cortical subset of the Visium HD dataset cortex <- SketchData(object = cortex, ncells = 50000, method = "LeverageScore", sketched.assay = "sketch") DefaultAssay(cortex) <- "sketch" cortex <- FindVariableFeatures(cortex) cortex <- ScaleData(cortex) cortex <- RunPCA(cortex, assay = "sketch", reduction.name = "pca.cortex.sketch", verbose = T) cortex <- FindNeighbors(cortex, reduction = "pca.cortex.sketch", dims = 1:50) cortex <- FindClusters(cortex, cluster.name = "seurat_cluster.sketched") cortex <- RunUMAP(cortex, reduction = "pca.cortex.sketch", reduction.name = "umap.cortex.sketch", return.model = T, dims = 1:50, verbose = T) DimPlot(cortex, label = T) # create the RCTD query object using 'SpatialRNA' function counts_hd <- cortex[["sketch"]]$counts cortex_cells_hd <- colnames(cortex[["sketch"]]) coords <- GetTissueCoordinates(cortex)[cortex_cells_hd, 1:2] query <- SpatialRNA(coords, counts_hd, colSums(counts_hd)) ### load in a scRNA-seq reference dataset ref <- readRDS("../Seurat/Visium_HD/allen_scRNAseq_ref.Rds") counts <- ref[["RNA"]]$counts view([email protected]) cluster <- as.factor(ref$subclass_label) levels(cluster) <- gsub("/", "-", levels(cluster)) # cluster <- droplevels(cluster) nUMI <- ref$nCount_RNA # create the RCTD reference object reference <- Reference(counts, cluster, nUMI) # Creating RCTD Object RCTD <- create.RCTD(query, reference, max_cores = 8) # max_cores: for parallel processing. # run RCTD RCTD <- run.RCTD(RCTD, doublet_mode = "doublet") # add results back to Seurat object cortex <- AddMetaData(cortex, metadata = RCTD@results$results_df) view([email protected]) DimPlot(cortex, label = T) DimPlot(cortex, group.by = "first_type", label = T) # change NA to Unknown cortex$first_type <- as.character(cortex$first_type) cortex$first_type[is.na(cortex$first_type)] <- "Unknown" DimPlot(cortex, group.by = "first_type", label = T) # project RCTD labels from sketched cortical cells to all cortical cells cortex <- ProjectData(object = cortex, assay = "Spatial.008um", full.reduction = "pca.cortex", sketched.assay = "sketch", sketched.reduction = "pca.cortex.sketch", umap.model = "umap.cortex.sketch", dims = 1:50, refdata = list(full_first_type = "first_type")) DefaultAssay(cortex) <- "Spatial.008um" view([email protected]) DimPlot(cortex, label = T, group.by = "full_first_type") SpatialDimPlot(cortex, group.by = "full_first_type", label = T, repel = T, label.size = 4)

professor, can u help me with this Integrating data Warning: Layer counts isn't present in the assay object; returning NULL Merging dataset 5 4 into 6 Extracting anchors for merged samples Finding integration vectors Error: std::bad_alloc

Very useful work sir. Continue doing it.

Professor,how do we get only 2 plot- control and IPF,I'm getting 6 of them

Professor,l am getting different cell type for the cluster shown in this video.Am l doing it wrong

Professor,what could be the reason for getting varying cluster number?Does the cluster no; effect our analysis

Professor,can't we merge the data before preforming quality control

Hello, Professor Thank you very much for sharing the videos and codes here. I have 2 question about the scenicOptions object. Since I perform the pyscenic analysis in singularity, there are 3 tsv files generated(adjacencies, regulons, auc_mtx), which uses the counts matrix get from seurat object. 1. How can I integrate this files to my seurat object to do next analysis as your video shows. Do I need to convert the seurat object to loom file? 2. I have 2 groups, how to compare between groups if I do scenic on whole expression matrix? I would be very grateful if you can provide any help. Thanks in advance. Best

Can you please explain to make CSI plot

Hi Professor, can I ask a question? After I get Differentially Expressed Genes, how can I connect the log2FC with original data in RDS to make heatmap?

How is umap and umaprpca different

Professor,how do we compare merged and integrated data in dimplot

Thank you! Very Good tutorial. Can you also explain how to construct network using exportNetworkoCytoscpe function? Or is there any other method to do so for further analysis?

When my computer executes the following code, it often freezes. adjacency = adjacency(datExpr, power = 6) TOM = TOMsimilarity(adjacency) My expression matrix has 13 samples and 20000 genes. How should I handle it? Thank you！！！

👍👍👍

I was about to run liana, and then found this video uploaded just 10hrs ago. What a miracle

library(liana) library(tidyverse) library(magrittr) show_resources() # cell-cell communication (CCC) Resources show_methods() # cell-cell communication (CCC) Methods ### liana takes Seurat and SCE objects as input, containing processed counts and clustered cells. liana_path <- system.file(package = "liana") testdata <- readRDS(file.path(liana_path , "testdata", "input", "testdata.rds")) # HUMAN PBMCs ### liana wrapper function # Run liana: returns a list of results, each element of which corresponds to a method liana_test <- liana_wrap(testdata) # call all methods that are currently available in liana. ### Aggregate and Obtain Consensus Ranks # We can aggregate these results into a tibble with consensus ranks liana_test <- liana_test %>% liana_aggregate() # RRA method from the RobustRankAggreg package ######## Visualization ### Simple DotPlot: interactions which are expressed in at least 10% of the cells liana_dotplot(liana_test, source_groups = c("B"), target_groups = c("NK", "CD8 T", "B"), ntop = 20) ### Frequency Heatmap: only keep interactions concordant between methods liana_trunc <- filter(liana_test, aggregate_rank <= 0.01) heat_freq(liana_trunc) ### Frequency Chord diagram p <- chord_freq(liana_trunc, source_groups = c("CD8 T", "NK", "B"), target_groups = c("CD8 T", "NK", "B"))

Will you continue the tutorial for microbiome analysis. Looking forward

can you perform tutorial for LIANA cell-cell communication too?

The polygons file is no longer available for download

Thanks for your video, I was able to run it following your demonstration.

Thank you. Please keep up the amazing work.

💯

your videos are excellent for beginners 👍👍👍

Hi Professor, thanks a lot for your video tutorial. Your explain for each step allows get the point explicitly. I have one question if I merged "control" dataset and "stimulated" dataset into one Seurat object for pre-processing workflow. In the following process, I should separate it into two dataset for PCA, UMAP, etc. Is it correct?

THX SO MUCH.

Thx for your demonstration

please continue to demonstrate how to create spliced/ unspliced data / loom files🙏

Quick question: I was following your tutorial closely but I couldn’t find where moduleColors. Where was this file produced? Thank you!

老师您讲解得真好！谢谢🙏

Thanks to you I became an expert bioinformatician in my lab!

Can someone please help me with this data set "GSE211033"? As when I use FindVaribaleFeatures I get the error " non-numeric argument to binary operator".

Hello Professor, Thanks for the great lecture. l had problems practicing it. After SplitObject, MergedNML S4[19232 x 11612] became MergedNML.list: NML_I [17574 x 3615], NML_II [18130 x 3993], NML_II [16665 x 4004]. The rows number was different, why?

Hi I used the merge function for my seurat objects but since the size is big it can't merge them. Could you please tell me how can I merge them?

Hello Professor, Thank you for your helpful videos. I have a question: Are you running SCENIC on Windows? After running the line scenicOptions <- runSCENIC_3_scoreCells(scenicOptions, exprMat_log), I get an error indicating that I need to install doMC package, which is not possible on Windows.

Very useful, thank you!

thanks for you videos, but you have lots of videos, I want to start from zero, but I lost. I wish you had a 4 hour videos from zero to hero

Hi thatnk for your great videos! I have a question. If in the download section for the data set there would not be custom section and the only available forms would be ftp and http how should we access these data sets? thanks

Thanks for sharing such an enlightening information and wonderful turorial!

Hi in most of available data sets they only provide (ftp)(http)formats. could you please tell me how can I access these three files in those cases if custom option is not provided? thanks

Hi thanks for your excellent videos! I have a question. Actually I have two groups, test and control. each of them has tumor samples of three mice which became mixed and then single cell analysis were done on them, so although there are three samples in each group, but I don't have p value for each group. could toy please tell me how can I have a volcano plot? thanks! And one more asking could you please teach Azimuth for annotation please?

Hello, thank you so much for your videos. They are really helpful. I used your tutorial to analyze my data, but I want to recluster some of my cells and I can't find a tutorial for it. Could you share a code or make a video about subset and recluster, please? Thank you!

Hi, I am new to this, I wanted to know there is a dataset GSE173706 in TAR (of CSV). How can we analysis this?