seurat subset downsample

How to subset the rows of my data frame based on a list of names? For your last question, I suggest you read this bioRxiv paper. Seurat Tutorial - 65k PBMCs - Parse Biosciences For the new folks out there used to Satija lab vignettes, I'll just call large.obj pbmc, and downsampled.obj, pbmc.downsampled, and replace size determined by the number of columns in another object with an integer, 2999: pbmc.subsampled <- pbmc[, sample(colnames(pbmc), size =2999, replace=F)], Thank you Tim. Try doing that, and see for yourself if the mean or the median remain the same. rev2023.5.1.43405. However, one of the clusters has ~10-fold more number of cells than the other one. Thanks, downsample is an input parameter from WhichCells, Maximum number of cells per identity class, default is Inf; downsampling will happen after all other operations, including inverting the cell selection. Monocle - GitHub Pages Why are players required to record the moves in World Championship Classical games? This works for me, with the metadata column being called "group", and "endo" being one possible group there. SubsetData : Return a subset of the Seurat object between numbers are present in the feature name, Maximum number of cells per identity class, default is The code could only make sense if the data is a square, equal number of rows and columns. Downsampling Seurat Object Issue #5312 satijalab/seurat GitHub Takes either a list of cells to use as a subset, or a parameter (for example, a gene), to subset on. inverting the cell selection, Random seed for downsampling. If ident.use = NULL, then Seurat looks at your actual object@ident (see Seurat::WhichCells, l.6). I managed to reduce the vignette pbmc from the from 2700 to 600. Subset a Seurat object RDocumentation. Ubuntu won't accept my choice of password, Identify blue/translucent jelly-like animal on beach. Takes either a list of cells to use as a subset, or a parameter (for example, a gene), to subset on. Number of cells to subsample. which command here is leading to randomization ? Is there a way to maybe pick a set number of cells (but randomly) from the larger cluster so that I am comparing a similar number of cells? You can then create a vector of cells including the sampled cells and the remaining cells, then subset your Seurat object using SubsetData() and compute the variable genes on this new Seurat object. Sign in to a point where your R doesn't crash, but that you loose the less cells), and then decreasing in the number of sampled cells and see if the results remain consistent and get recapitulated by lower number of cells. Cannot find cells provided, Any help or guidance would be appreciated. Identify cells matching certain criteria WhichCells you may need to wrap feature names in backticks (``) if dashes If I always end up with the same mean and median (UMI) then is it truly random sampling? expression: . Again, Id like to confirm that it randomly samples! I followed the example in #243, however this issue used a previous version of Seurat and the code didn't work as-is. Not the answer you're looking for? For example, Thanks for this, but I really want to understand more how the downsample function actualy works. To subscribe to this RSS feed, copy and paste this URL into your RSS reader. exp2 Micro 1000 cells Sign in If the null hypothesis is never really true, is there a point to using a statistical test without a priori power analysis? Logical expression indicating features/variables to keep, Extra parameters passed to WhichCells, such as slot, invert, or downsample. Seurat (version 3.1.4) Description. For more information on customizing the embed code, read Embedding Snippets. I checked the active.ident to make sure the identity has not shifted to any other column, but still I am getting the error? Sign up for a free GitHub account to open an issue and contact its maintainers and the community. I meant for you to try your original code for Dbh.pos, but alter Dbh.neg to, Still show the same problem: Dbh.pos <- Idents(my.data, WhichCells(my.data, expression = Dbh >0, slot = "data")) Error in CheckDots() : No named arguments passed Dbh.neg <- Idents(my.data, WhichCells(my.data, expression = Dbh == 0, slot = "data")) Error in CheckDots() : No named arguments passed, HmmmEasier to troubleshoot if you would post a, how to make a subset of cells expressing certain gene in seurat R, How a top-ranked engineering school reimagined CS curriculum (Ep. = 1000). By clicking Accept all cookies, you agree Stack Exchange can store cookies on your device and disclose information in accordance with our Cookie Policy. Thank you for the suggestion. Yes it does randomly sample (using the sample() function from base). For this application, using SubsetData is fine, it seems from your answers. Already on GitHub? By clicking Sign up for GitHub, you agree to our terms of service and Generating points along line with specifying the origin of point generation in QGIS. It only takes a minute to sign up. This is called feature selection, and it has a major impact in the shape of the trajectory. I can figure out what it is by doing the following: meta_data = colnames (seurat_object@meta.data) [grepl ("DF.classification", colnames (seurat_object@meta.data))] Where meta_data = 'DF.classifications_0.25_0.03_252' and is a character class. The text was updated successfully, but these errors were encountered: This is more of a general R question than a question directly related to Seurat, but i will try to give you an idea. If the null hypothesis is never really true, is there a point to using a statistical test without a priori power analysis? Have a question about this project? to your account. Step 1: choosing genes that define progress. Which language's style guidelines should be used when writing code that is supposed to be called from another language? Why the obscure but specific description of Jane Doe II in the original complaint for Westenbroek v. Kappa Kappa Gamma Fraternity? To learn more, see our tips on writing great answers. 1 comment bari89 commented on Nov 18, 2021 mhkowalski closed this as completed on Nov 19, 2021 Sign up for free to join this conversation on GitHub . accept.value = NULL, max.cells.per.ident = Inf, random.seed = 1, ). Hi Leon, However, when I try to do any of the following: seurat_object <- subset (seurat_object, subset = meta . which, lets suppose, gives you 8 clusters), and would like to subset your dataset using the code you wrote, and assuming that all clusters are formed of at least 1000 cells, your final Seurat object will include 8000 cells. Learn more about Stack Overflow the company, and our products. Find centralized, trusted content and collaborate around the technologies you use most. Why don't we use the 7805 for car phone chargers? Subsets a Seurat object containing Spatial Transcriptomics data while [: Simple subsetter for Seurat objects [ [: Metadata and associated object accessor dim (Seurat): Number of cells and features for the active assay dimnames (Seurat): The cell and feature names for the active assay head (Seurat): Get the first rows of cell-level metadata merge (Seurat): Merge two or more Seurat objects together If you make a dataframe containing the barcodes, conditions, and celltypes, you can sample 1000 cells within each condition/ celltype. You can then create a vector of cells including the sampled cells and the remaining cells, then subset your Seurat object using SubsetData() and compute the variable genes on this new Seurat object. WhichCells function - RDocumentation Making statements based on opinion; back them up with references or personal experience. This is what worked for me: downsampled.obj <- large.obj[, sample(colnames(large.obj), size = ncol(small.obj), replace=F))]. FilterCells function - RDocumentation Already on GitHub? A stupid suggestion, but did you try to give it as a string ? My question is Is this randomized ? How are engines numbered on Starship and Super Heavy? Related question: "SubsetData" cannot be directly used to randomly sample 1000 cells (let's say) from a larger object? 565), Improving the copy in the close modal and post notices - 2023 edition, New blog post from our CEO Prashanth: Community is the future of AI. Developed by Rahul Satija, Andrew Butler, Paul Hoffman, Tim Stuart. By clicking Post Your Answer, you agree to our terms of service, privacy policy and cookie policy. For the dispersion based methods in their default workflows, Seurat passes the cutoffs whereas Cell Ranger passes n_top_genes. Why are players required to record the moves in World Championship Classical games? Asking for help, clarification, or responding to other answers. What are the advantages of running a power tool on 240 V vs 120 V? Default is INF. Sample UMI SampleUMI Seurat - Satija Lab Is a downhill scooter lighter than a downhill MTB with same performance? Seurat: Error in FetchData.Seurat(object = object, vars = unique(x = expr.char[vars.use]), : None of the requested variables were found: Ubiquitous regulation of highly specific marker genes. - Sign up for a free GitHub account to open an issue and contact its maintainers and the community. rev2023.5.1.43405. The text was updated successfully, but these errors were encountered: I guess you can randomly sample your cells from that cluster using sample() (from the base in R). DownsampleSeurat: Downsample Seurat in bimberlabinternal/CellMembrane clusters or whichever idents are chosen), and then for each of those groups calls sample if it contains more than the requested number of cells. If there are insufficient cells to achieve the target min.group.size, only the available cells are retained. Short story about swapping bodies as a job; the person who hires the main character misuses his body. This tutorial is meant to give a general overview of each step involved in analyzing a digital gene expression (DGE) matrix generated from a Parse Biosciences single cell whole transcription experiment.