Getassaydata seurat v5 github. Reload to refresh your session.
Getassaydata seurat v5 github The v5 Assay Object. That is the neat solution I am looking for. I'm not sure if it has anything to do with the version of Seurat, because I ran this step with v4 before without any problems All reactions Community-provided extensions to Seurat. The volcano plots of a few of the clusters show a large number genes with low (significant) p-values despite Subset Seurat Objects. Cells() Features() Cell and Feature Names. By setting a global option (Seurat. data'). 0 and Seurat version is 3. The cell This function can be used to pull information from any of the slots in the Assay class. I had originally integrated two datasets (2 different conditions) using the standard workflow, and there we Hello, Thank you for the fantastic package of Seurat. Do you have a branch going with any in-progress changes? I would be happy to try to contribute code as we encounter issues. In Seurat v5, we include support for the v5 assay class, which can flexibly store data in a variety of formats (including disk-backed formats). I got the error Error in First, GetAssayData has been superseded by LayerData so suggest moving to that when using V5 structure moving forward. While on the fact of it a one cell assay might not seem useful, the inability to support it does cause headaches when using a seurat object to handle data. As a result, users will observe **higher logFC estimates** in v5 - but should note that these estimates may be more unstable - particularly for genes that are very lowly expressed in one of the two groups Hi @naamama I am not part of the SingleR team but I assume you installed SingleR using the Bioconductor release. I am using seuratv5 on server, but find many packages are unable to run for seuratv5 object. As my case, i want to remove the cell cycle influence for data integrated of clustering, so, should i run the CellCycleScoring function before samples integrated or after the data integrated. For Seurat v5, I think it will be working if you execute below codes and Dashboard for single cell analysis using Seurat. The 'CreateSinglerObject' has been removed when the code was rewritten and you now need to The FindVariableFeatures() when executed with v5 assay does not find variable features based on standardized variance. matrix(GetAssayData(data, slot = "data")) scale. You signed in with another tab or window. We will use Seurat objects containing the metacells counts data and their annotation (e. Accurate and fast cell marker gene identification with COSG. 2, but installed Seurat 4. This vignette demonstrates analysing RNA Velocity quantifications stored in a Seurat object. Best, Sam. In this way the object is expected to contain all of the cells/images overall but layers are split as needed. Various utility functions for Seurat single-cell analysis - vertesy/Seurat. Contribute to satijalab/seurat development by creating an account on GitHub. In that case I would ignore the guides on this Github repository and focus on the vignette from the SingleR bioconductor page. Creating V5 assay in Seurat Object. R toolkit for single cell genomics. Hello! I am working with some ATAC samples and I wanted to integrate them using the IntegrateLayers function. I previously had Seurat 4. seu <- merge(x=seu_list[[1]], y=seu_list[2 写在前面. Now i have Seurat 2. Seurat v5 assays store data in layers. Below is the code. #> ℹ Please use the `layer` argument instead. Layers in the Seurat v5 object. Seurat: Convert objects to Seurat objects; as. 1. The first is within Seurat’s spatial framework (see here and here) and requires a Seurat object and a lambda parameter as mandatory input. A vignette about moving and sharing Seurat objects would In reference to #26, GetAssayData() in predict_query. counts <- GetAssayData(xenium. The second option works with Seurat objects that do You signed in with another tab or window. I am opening this issue as a notification because scRNAseqApp is listed here as a package that relies (depends/imports/suggests) on Seurat. You switched accounts on another tab or window. My current R version is R/3. Hi ! I'm trying to run PAGA on my single cell dataset. I found that I need to use layer instead of slot, so I figure you have updated the terminology: LayerData(, layer = "count") We are currently working with Seurat v5 and encountering a notable discrepancy in the output size between DESeq2 and MAST when performing differential expression (DE) analysis. I create a unified set of peaks for the data to remove the a Contribute to satijalab/seurat development by creating an account on GitHub. by='seur In Seurat v5, merging creates a single object, but keeps the expression information split into different layers for integration. Summary information about Seurat objects can be had quickly and easily using standard R functions. Update Reading the code of GetAssayData, I realise that it only works for "raw. Some of my collaborators enjoy seeing average expression of the genes in each cluster, and would like the FeaturePlots scale to match their spreadsheets. Sign up for GitHub The Seurat package (version >= 3. New data must have the same cells in the same order as the Hi Samuel, Thanks again for all your help. Sign up for a free GitHub account to open an issue and contact its maintainers and the community. AverageExpression: Averaged feature expression by identity class I am using Seurat version 5 and have a v5 assay that I have calculations on and Integrated with the new v5 integration method for Harmony. Storing a custom dimensional reduction Seurat v5. flavor='v2' Thanks you @reberya! I've been stuck with this issue for hours! I really don't understand why doing this would work so especially because I did the same merge with other samples coming from different tissues (but from the same batch, and they all got exactly the same preprocessing), and only for a subset of these I got this issue doesn't male sense to me In reference to #26, GetAssayData() in predict_query. R GetAssayData() inline with Seurat v5. Contribute to satijalab/seurat-wrappers development by creating an account on GitHub. Run rlang::last_trace() to see where the error occurred. Saved searches Use saved searches to filter your results more quickly Create Seurat or Assay objects. data"). 4. obj, assay = "Xenium", slot = "counts")[, Cells(xenium. method = "vst", nfeatures = 2000) My understanding : This function compute a score for each gene to select the 2000 bests for the next step, the PCA Hello, I am trying to merge 4 rds of mine after reading them in. SetAssayData can be used to replace one of these expression matrices Explore the GitHub Discussions forum for satijalab seurat in the Q A category. To solve the problem try using the functions of the newest version of seurat v5. @mojaveazure Thank you for your reply,I follow your advice and download the the loom branch of Seurat ,but it still failed to convert this loom file to a Seurat object. I've a list of 7 Seurat objects from 10X spatial datasets, and ran SCTransform on them. In both my own dataset and the publicly available pbmcsca dataset from the SeuratData package, with Seurat v5. # keep cells with at least 6 genes with 1 or more counts cs <- GetAssayData can be used to pull information from any of the expression matrices (eg. Assay5-validity. Hi @corinnestrawser this is due to Seurat V5 updated its data accessor Hi, I'm running into an issue with Seurat::CellCycleScoring() in Seurat V5. If you use velocyto in your work, please cite: Saved searches Use saved searches to filter your results more quickly You signed in with another tab or window. Object shape/dimensions can be found using the dim, ncol, and nrow functions; cell and feature names can be found using the colnames and rownames functions, respectively, or the dimnames function. pcs <-prcomp (x = data) pca. I'm updating my script, which I wrote for SeuratV4 to accommodate the changes to Seurat V5. , by read Hi Chan, You can use the FetchData function to get the info you are after. For example, the command GetAssayData(obj, assay="RNA", slot='counts'), will run successfully The v5 Assay is the typical Assay class used in Seurat v5; A named list containing expression matrices; each matrix should be a two-dimensional object containing some subset of cells and We will use Seurat objects containing the metacells counts data and their annotation (e. I would personally remove those genes from the matrix prior to importing it in Seurat. In addition, in Seurat v5 we implement a **pseudocount** (when calculating log-FC) at the **group level** instead of the cell level. by column group. You signed out in another tab or window. , scRNA-seq, scATAC-seq and spatially resolved transcriptome data. Also, the column names are the same between assay_data_all and additional_genes_matrix. g. The main function of Augur, calculate_auc, takes as input a preprocessed features-by-cells (e. 1) on stimulated vs. csv") @jjo12 If you want to do by cluster then you can simply subset the matrix extracted from Seurat object by cell names from that cluster before saving the file. e. However my seurat object was created with v3. I noticed that the SeuratToExpressionSet doesn't seem to work with seurat v5 objects. 3) should take care of Seurat in multiple layers. Great software, but I've run into an issue I can't find documented anywhere here. Assay5 objects (see here). data, @smorabit: I'm not sure how much time you've had to spend on this migration, but I recently migrated a handful of my lab's R packages to be compatible with Seurat 5. raw. Due to the vignette describing loading h5ad files rather than h5, I encountered some issues during loading and analysis. The v5 Assay Class and Interaction Methods . R needs updating to access 'data' as a Seurat v5 layer rather than an assay. 9. When I use LayerData(, slot = "count"), it returns the "data". Although my data is a little bit different, I am still comparing two groups in this case Adult v. sparse: Convert between data frames and sparse matrices; AugmentPlot: Augments ggplot2-based plot with a PNG image. The primary issue I found in my first look at using this with Seurat 5 was their layering Accessing data from an Assay object is done in several ways. Our workflow involves: Using DESeq2 with pseudobulk raw coun Since feature names are not easily changeable in Seurat, I would recommend either creating a new Seurat object with the modified counts matrix or adding it as a new assay (see our multimodal analysis vignette for more details about working with multiple assays). This is how the object looks like before the integration step I previously posted some additional info in SeuratObject github on differences between adding feature level meta data for Assay vs. New data must have the same cells in the mat <- GetAssayData(object = pbmc, assay = "RNA", slot = "data") write. Hello, thank you for the tool. data <- GetAssayData(object In Seurat v5, we introduce new infrastructure and methods to analyze, interpret, and explore datasets that extend to millions of cells. 2. Parameters are based off of the RNA Velocity tutorial. ids` parameter with an `c(x, y)` vector, which will prepend the given identifier to the beginning of each cell name. The pipeline includes normalization, pseudobulk creation, clustering, heatmap generation, and principal component analysis (PCA). Then access the desired data matrix with the GetAssayData function. Seurat(assay = slot) Run rlang::last_trace(drop = FALSE) to see 4 hidden frames. I noticed the default layer used by FetchData in Seurat V5 (for Assay5 objects) seems to be the counts layer. 0. I *think* the latest version on GitHub (2. We are closing this issue now as we are no longer prioritizing support for loom conversion. As you may know, we recently released Seurat v5 as a beta in March of this year, with new updates for spatial, multimodal, and massively scalable analysis. I am now using LayerData() instead of GetAssayData() as advised in the Lifecycle note. Note that in plot1 the top 10 variable features are randomly dispersed, unlike plot2 generated with Hello Seurat Team, and thank you for the new version! At this point, working with datasets in different layers (for example different samples) is quite cumbersome when it comes to applying different functions (seurat Navigation Menu Toggle navigation. Here It looks like you're using a really old version of the Seurat v3 alpha, before the conversion functions were updated for the v3 object. Plots were generated. Therefore, in Issue #5, I generated new codes for calculate_avg_exp() function by editing its source codes. Adding expression data to either the counts, data, or scale. table <- GetAssayData(data1 , slot = "scale. It seems that this loom edition is rare,and there is little help documentation about how to convert loom to seurat. integrated, assay = "RNA", slot = "data") # normalized data matrix labels <- Idents(allbiopsies. Also, I slightly changed these codes, from Issue #5, in order to get counts matrix from seurat v5 object. table<- as. eset <- BisqueRNA::SeuratToExpressionSet(re General accessor and setter functions for Assay objects. I suggest checking out the manual entry for FetchData and the Wiki page to understand that slot/data structure of Seurat objects. method = "vst", nfeatures = 2000, verbose = FALSE) Hi, People have found a similar issue here: #1029 You can try a workaround but we have now introduced multiple ways to scale-up the integration, using either reference-based integration or reciprocal PCA rather Hi merge just concatenates the counts or data table from two object together. Pulling expression data from the data slot can also be done with the single [extract operator. Seurat COSG is a cosine similarity-based method for more accurate and scalable marker gene identification. The use of v5 assays is set by default upon package loading, which ensures backwards compatibiltiy with existing workflows. Unfortunately this algorithm works only with Seurat version2. This means that in order to use Augur, you should have pre-processed your data (e. 1 then everything began to work normally again. I want to convert into seurat v4 and run packages on my local laptop. Running SCTransform on layer: counts. 1 users who also have Azimuth and/or Signac installed may encounter the following error: object 'CRsparse_colSums' not found when trying to run colSums or rowSums on any dgCMatrix. Also, I think METAFlux package is not compatible with Seurat v5, yet. I'm integrating 8 datasets following the integration vignette. In this way the object is expected to contain all of the data <-GetAssayData (pbmc_small [["RNA"]], slot = "scale. Hi Tim, I am having the exact same issue with 10X data too. If either object has unique genes, it will be added in the merged objects. cell-type annotation) and proceed with standard Seurat downstream analyses. I am using Seurat V5 and Signac for the processing of the samples. utils Hi, is it possible, and how, to take data from one of the features (for example - a feature antibody data) from Seurat object and add it back to the same object, but as a separate assay? Thanks for the help, Gloria Sign up for a free GitHub account to open an issue and contact its maintainers and the community. data Counts matrix provided is not sparse. Each of these have 4 samples in them that are QC'd but unintegrated and SCTransformed, and have run pca, clustered and umap ran. These layers can store raw, un-normalized counts (layer='counts'), normalized data (layer='data'), or z-scored/variance-stabilized data (layer='scale. Thanks in advance! Best, Michelle The purpose of posting is to ask your team to consider re-enabling this case with V5 assays. data" but the documentation vaguely suggests by its use of ellipsis that it works for more options than just those three:. ES_030_p4 vst. Additionally, I couldn't find a "GetAssay. object. I can use the SCTransform v2 and integration workflow to mitigate these effects. “counts”, “data”, or “scale. The FIndVariableFeatures command for each of the Seurat objects was FindVariableFeatures(seurat_objects[[samplename]], selection. SingleCellExperiment: Convert objects to SingleCellExperiment objects; as. Assay5-class Assay5. We include multiple examples for disk-backed analysis using the BPCells package from Ben Parks . Is My seurat version is V5. as. cell. It worked fine in Seurat V4, but now produces the following error: > sc_obj An object of class Seurat 23341 features across 17601 samples within 1 assay Active a Hi all. joined<-JoinLayers(integrated. 去批次的方法Seuratv5包含了以下几个方法： 3. version), you can default to creating either Seurat v3 assays, or Seurat v5 assays. When I try to load th In my case, when using an integrated object I firstly join the layers as Azimuth doesn't seem to accept multiple layers objects: integrated. #just to check what version you are actually using packageVersion('Seurat') Note from Dev: Thank you everyone for your support and use of scCustomize, I’m really happy so many people find it useful! As many of you are aware the Satija lab released a major update to Seurat in the form of Seurat V5 (currently in b Then you could use write. . I was wondering if there is a work around or fix for this? Thank you!! sc. obj[["crop"]])] but also by their broader spatial context. This suggestion is invalid because no changes were made to the code. The addition is just overriding the I am confused about the following since updating to Seurat_4. COSG is a cosine similarity-based method for more accurate and scalable marker gene identification. Thank you Gesmira for your reply, do you mean that using IntegrateLayers() to replace two statements, FindIntegrationAnchors() and IntegrateData()? By clicking “Sign up for GitHub”, GetAssayData. If you'd like to use as. In my script, I want to perform CellCycleScoring prior to SCT so I can regress out the cell-cycle score. Contribute to satijalab/seurat-object development by creating an account on GitHub. ```{r merging-2, eval=FALSE, results = 'hide'} Hello, I have a v5 seurat object with one assay (RNA) and 27 layers. If not proceeding with integration, rejoin the layers after merging. integrated) Hi, I have eight samples (AW1 to AW8), these represent four experimental groups, two biological replicates in each group (T1 to T4; T1=AW1+AW2, T2=AW3+AW4, T3=AW5+AW6, T4=AW7+AW8). This issue should be linked with both #8004 and #7936, but this case is slightly different as I am only working with v5 objects and I am not trying to save. A vector of names of Assay, DimReduc, and Graph `merge()` merges the raw count matrices of two `Seurat` objects and creates a new `Seurat` object with the resulting combined raw count matrix. We introduce support for 'sketch-based' techniques, where a subset of representative cells are stored in memory to enable rapid and iterative exploration, while the remaining cells are stored on-disk. GetAssayData can be used to pull information from any of the expression matrices (eg. Navigation Menu Sign up for a free GitHub account to open an issue and contact its maintainers and the community. However, I found it only returns the normalised expression, but not the RAW data? Hi, I would like to understand the algorithm behind FindVariableFeatures(pbmc, selection. 4 installed in a different location. Skip to content. data. GetAssayData doesn't work for multiple layers in v5 assay. To easily tell which original object any particular cell came from, you can set the `add. If you want the expression values for certain genes for just cells in cluster 13, make a new Seurat object with the desired cells and features using the Seurat subset function. data") — You are receiving You signed in with another tab or window. R GetAssayData() inline with Seurat v5 tfguinan Jan 18 You signed in with another tab or window. 7. i. , genes-by-cells for scRNA-seq) matrix, and a data frame containing metadata associated with each cell, minimally including the cell type annotations and sample labels to be predicted. Hi, I recently switch to Seurat V5 and found out that the current version of scigenex is not compatible with this new version, in which object data access / slots have changed (GetAssayData() is deprecated and "slots" are "layers" ). 3. Thanks Sam. I would now like to output a table Hi @ktrns, Sorry for the unclear description. In earlier seurat versions, I would run this: obj <- ScaleData(obj,features = rownames(obj)) but now when I Hi I follow the Seurat V5 Vignette Using BPCells with Seurat Objects to load 10 Cell Ranger filtered h5 files. 0) is used for loading data and preprocessing. In our analysis, we split our samples into healthy and disease states and created a separate object for each category. 1 Load metacell Seurat object. 👍 4 lzmcboy, antecede, erdaqorri, and RunzheWang reacted with thumbs up emoji R toolkit for single cell genomics. Hello, I have a question regarding SetDataExpr function. Seurat::GetAssayData(seu, "counts") should work with Seurat v3, v4, v5 since this function is updated with each new release of Seurat. input <- GetAssayData(allbiopsies. I see the following output for each of the 27 layers, showing that the SCTransform has successfully run. Reload to refresh your session. table function or any other functions to write them into csv files. I think maybe it is difficult to convert directly, but I couldn't be able to Accessing data from an Assay object is done in several ways. Then by using merge we combined the Seurat objects and proceeded with the pipeline available in Seurat for the integration. IntegrateData is a step in the integration, integrating two objects by anchor cells. I noticed that I get You signed in with another tab or window. Hi, I'm running Cell-Cycle Scoring (Seurat version 3. In reference to #26, GetAssayData() in predict_query. I read Error: GetAssayData doesn't work for multiple layers in v5 assay The text was updated successfully, but these errors were encountered: All reactions I believe the above will still utilize only the features extracted from SelectIntegrationFeatures rather than using all features that might be noisy (and defeat the purpose of using SCTransform). CastAssay() GetAssayData() SetAssayData() Get and Set Assay Data. What could be the problem? If create_condaenv_seuratextend() is failing to create the ‘seuratextend’ conda environment, it might be due to the system not finding conda or git. no applicable method for 'GetAssayData' applied to an object of class "seurat" Is this a problem with the version or am I doing something wrong? Thank you in advance! Sign up for free to join this conversation on GitHub. Running this code: Prep_Healthy<- Hello Seurat Team, Fairly new to this, so I apologize if this has been addressed before. Hi, thank you for the work in developing and updating the Seurat application. dr <-CreateDimReducObject (embeddings = pcs $ rotation, loadings = pcs $ x, stdev = pcs $ sdev, key = "PC", assay = "RNA") #> Warning: Keys should Add this suggestion to a batch that can be applied as a single commit. SetAssayData can be used to replace one of these expression Add in metadata associated with either cells or features. control datasets and I would like to see how phases are distributed on WT and KO (in each cluster). 0 I see what looks like a "shift" in the avg_log2FC values of some clusters when running the default Wilcoxon test with FindAllMarkers. For example, pull one of the data matrices ("counts", "data", or "scale. We describe two options of running RunBanksy. The detail you could find in the paper, here. Seurat" function but I did find one named "GetAssayData" so I'm not sure how to proceed with debugging for my current analysis. Hello Seurat team, I am working with a dataset that contains multiple experiments and has batch effects. Already have an account? The RunBanksy function implemented with the SeuratWrappers package allows users to run BANKSY with Seurat objects. In Seurat v5, we introduce support for 'niche' analysis of spatial data, which demarcates regions of tissue How can I modify or open the seurat RDS object after moving the folder around? It probably stems from my limited understanding of the BPCells and Seurat v5 object structures. The object obtained from IntegrateData only contains anchor genes, which can be set in the Community-provided extensions to Seurat. CellsByIdentities() Get cell names grouped by identity class. Contribute to pritampanda15/CellGuide development by creating an account on GitHub. query. I know UpdateSe After upgrading to Seurat/SeuratObject v5. We can load in the data, remove low-quality cells, and obtain predicted cell annotations (which will be useful for assessing integration You signed in with another tab or window. data slots can be done with SetAssayData. You are right, I missed this part of the vignette thanks. Hello, I am wondering how to use the ScaleData() function to scale all genes in Seurat version 5, and not just variable features. I haven't seen this issue before when I have used RunCCA on v2. Sign in Product #Extract the CellChat input files from a Seurat object #The normalized count data and cell group information can be obtained from the Seurat object by. 1). I also agree would be helpful if Seurat team added this to vignette but the issues as specified in your original post are normal behavior for website and function manual. if i run before data integrated, it would be run CellCycleScoring for each sample and running integrated workflow to merge multiple samples Counts matrix provided is not sparse. Since I have integrated Seurat object from control and mutant my colnames are for In reference to #26, GetAssayData() in predict_query. In Seurat V5 SplitObject is no longer used and it is layers within that are split. When I run GetAssayData() using Seurat v5 object sce <- GetAssayData(object = obj, assay = "RNA") to use SingleR package for annotation. We are exploring ways of allowing users to easily change cell and feature names, but have nothing to Community-provided extensions to Seurat. Warning: Removing default layer, setting default to scale. The list is "Prep_Healthy". Latest version: The latest developmental version of Scissor can be downloaded from GitHub and installed from source by devtools::install_github('sunduanchen/Scissor') Compiled: July 15, 2019. If that's not an option, you could retrieve the counts from your Seurat object with: counts <- GetAssayData(seurat_obj, assay = "RNA) Find out the index of the genes you want removed:. For v5 assay please use LayerData () for extraction. This in turn R toolkit for single cell genomics. data”). 6. Suggestions cannot be applied while the pull request is closed. object) Hi, I'm fairly new to R and Seurat, so I hope this will be an easy fix. I run : ###Set up the expression matrix seurat_obj <- SetDatExpr( seurat_obj, group_name = "Adipocytes_2", # the name of the group of interest in the group. I have run an integrated analysis on all the samples and You signed in with another tab or window. 啊~囧，就拿Integrative analysis来进行测试展示吧！ Integrative analysis. It turns out that the Layer "data" had moved from the Assay "RNA" to the Assay "SCT_Reg" which I generate using SCTransform(). When I was using Seurat to merge samples as Seurat Objects within seu_list, the merge function didn't work properly. Everything works fine until I get to the IntegrateLayers step, and I get the followi Hi, Thank you for the great tool. 9041 (using RStudio with R version 4. If I'm not mistaken, this might break certain functions, in my case using the DotPlot visualization which uses Seurat is an R toolkit for single cell genomics, developed and maintained by the Satija Lab at NYGC. COSG is a general method for cell marker gene identification across different data modalities, e. Expression data is accessed with the GetAssayData function. Update project_query. R GetAssayData() inline with Seurat v5 Q: The create_condaenv_seuratextend() function is failing to create the ‘seuratextend’ conda environment. V5 Assay Validity. data, data, scale. 77c95d5. Any help would be greatly appreciated. data") #> Warning: The `slot` argument of `GetAssayData()` is deprecated as of SeuratObject 5. However, I would prefer to keep a list of Seurat objects for the first few steps, which is in may case filtering based on mitochondrial # Pseudobulk Analysis Pipeline with Seurat v5 This repository contains an automated pipeline for pseudobulk analysis and downstream unsupervised analysis using Seurat v5. Is an object global/persistent? Existing Seurat functions and workflows from v4 continue to work in v5. packages However, in order to project velocities on the integrated Seurat object, colnames on loom and Seurat objects need to match. Second, as pointed out here by dev team in order to pull data from all applicable layers GetAssayData doesn't work for multiple layers in v5 assay. I've encountered similar issue. Thank you so much! I did normalise and scale the object before attempting the integration, and the same piece of code was working in the beta version of Seurat. We are excited to release Seurat v5! This updates introduces new functionality for spatial, multimodal, and scalable single-cell Thank you @Gesmira. I used to do something like this to discard cells with too few genes or genes with too few cells. Can you try to install from github (remotes::install_github("carmonalab/UCell") and see whether it works for you? You signed in with another tab or window. SingleCellExperiment on a Seurat v3 object, I recommend upgrading to any of the released versions of Seurat v3 using either remotes::install_version or install. assay. Is there a different way to approach this? I am using Seurat v5, and I have confirmed that in updated_expr_matrix, the additional genes are being appended as rows to the end. Also, thank you for such a good program. csv(mat, "mat. data", "data" and "scale. However, I would like to convert it back to a v3 assay, just to plot UMAP's and find up regulated genes in each cluster. iszc tybv mylyt led aqsnhj gakjz mjkp nbwrz cqtp vbxpou