# Subset Seurat object based on identity class, also see ?SubsetData subset (x = pbmc, idents = "B cells") subset (x = pbmc, idents = c ("CD4 T cells", "CD8 T cells"), invert = TRUE) subset (x = pbmc, subset = MS4A1 > 3) subset (x = pbmc, subset = MS4A1 > 3 & PC1 > 5) subset (x = pbmc, subset = MS4A1 > 3, idents = "B cells") subset (x = pbmc, Already on GitHub? I managed to reduce the vignette pbmc from the from 2700 to 600. privacy statement. 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: I was trying to do the same and is used your code. Numeric [0,1]. Browse other questions tagged, Where developers & technologists share private knowledge with coworkers, Reach developers & technologists worldwide, I try this and show another error: Dbh.pos <- Idents(my.data, WhichCells(my.data, expression = Dbh == >0, slot = "data")) Error: unexpected '>' in "Dbh.pos <- Idents(my.data, WhichCells(my.data, expression = Dbh == >", Looks like you altered Dbh.pos? Additional arguments to be passed to FetchData (for example, If the null hypothesis is never really true, is there a point to using a statistical test without a priori power analysis? 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. How to force Unity Editor/TestRunner to run at full speed when in background? By clicking Sign up for GitHub, you agree to our terms of service and Creates a Seurat object containing only a subset of the cells in the original object. I checked the active.ident to make sure the identity has not shifted to any other column, but still I am getting the error? So if you clustered your cells (e.g. I actually did not need to randomly sample clusters but instead I wanted to randomly sample an object - for me my starting object after filtering. MathJax reference. Returns a list of cells that match a particular set of criteria such as Here we present an example analysis of 65k peripheral blood mononuclear blood cells (PBMCs) using the R package Seurat. Cannot find cells provided, Any help or guidance would be appreciated. I dont have much choice, its either that or my R crashes with so many cells. Sign up for a free GitHub account to open an issue and contact its maintainers and the community. Thanks again for any help! Thanks for the wonderful package. Already have an account? Default is INF. They actually both fail due to syntax errors, yours included @williamsdrake . For ex., 50k or 60k. To subscribe to this RSS feed, copy and paste this URL into your RSS reader. Seurat (version 3.1.4) Description. For more information on customizing the embed code, read Embedding Snippets. subset.name = NULL, accept.low = -Inf, accept.high = Inf, = 1000). - zx8754. 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. Thanks for the answer! However, one of the clusters has ~10-fold more number of cells than the other one. For more information on customizing the embed code, read Embedding Snippets. Any argument that can be retreived Downsample each cell to a specified number of UMIs. With Seurat, you can easily switch between different assays at the single cell level (such as ADT counts from CITE-seq, or integrated/batch-corrected data). Why the obscure but specific description of Jane Doe II in the original complaint for Westenbroek v. Kappa Kappa Gamma Fraternity? Use MathJax to format equations. Does it not? You signed in with another tab or window. To use subset on a Seurat object, (see ?subset.Seurat) , you have to provide: What you have should work, but try calling the actual function (in case there are packages that clash): Thanks for contributing an answer to Bioinformatics Stack Exchange! What pareameters are excluding these cells? Usage 1 2 3 Sign up for a free GitHub account to open an issue and contact its maintainers and the community. Downsampling one of the sample on the UMAP clustering to match the If I always end up with the same mean and median (UMI) then is it truly random sampling? 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. Subsets a Seurat object containing Spatial Transcriptomics data while SeuratCCA. Seurat part 4 - Cell clustering - NGS Analysis 1) The downsampled percentage of cells in WT and KO is more over same compared to the actual % of cells in WT and KO 2) In each versions, I have highlighted the KO cells for cluster 1, 4, 5, 6 and 7 where the downsampled number is less than the WT cells. to your account. Sign up for a free GitHub account to open an issue and contact its maintainers and the community. Single-cell RNA-seq: Integration It's a closed issue, but I stumbled across the same question as well, and went on to find the answer. subset_deg <- function(obj . The steps in the Seurat integration workflow are outlined in the figure below: DEG. between numbers are present in the feature name, Maximum number of cells per identity class, default is just "BC03" ? I am pretty new to Seurat. Is it safe to publish research papers in cooperation with Russian academics? Why don't we use the 7805 for car phone chargers? Yes it does randomly sample (using the sample() function from base). This is called feature selection, and it has a major impact in the shape of the trajectory. seuratObj: The seurat object. Stack Exchange network consists of 181 Q&A communities including Stack Overflow, the largest, most trusted online community for developers to learn, share their knowledge, and build their careers. Well occasionally send you account related emails. I think this is basically what you did, but I think this looks a little nicer. identity class, high/low values for particular PCs, etc. [.Seurat function - RDocumentation Is a downhill scooter lighter than a downhill MTB with same performance? This works for me, with the metadata column being called "group", and "endo" being one possible group there. 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. Site design / logo 2023 Stack Exchange Inc; user contributions licensed under CC BY-SA. However, you have to know that for reproducibility, a random seed is set (in this case random.seed = 1). Also, please provide a reproducible example data for testing, dput (myData). Should I re-do this cinched PEX connection? However, if you did not compute FindClusters() yet, all your cells would show the information stored in object@meta.data$orig.ident in the object@ident slot. downsample: Maximum number of cells per identity class, default is Inf; downsampling will happen after all other operations, . 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. Already on GitHub? RDocumentation. 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. This is what worked for me: downsampled.obj <- large.obj[, sample(colnames(large.obj), size = ncol(small.obj), replace=F))]. However, to avoid cases where you might have different orig.ident stored in the object@meta.data slot, which happened in my case, I suggest you create a new column where you have the same identity for all your cells, and set the identity of all your cells to that identity. Hi, I guess you can randomly sample your cells from that cluster using sample() (from the base in R). Thank you. If you make a dataframe containing the barcodes, conditions, and celltypes, you can sample 1000 cells within each condition/ celltype. They actually both fail due to syntax errors, yours included @williamsdrake . Meta data grouping variable in which min.group.size will be enforced. 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. Cell types: Micro, Astro, Oligo, Endo, InN, ExN, Pericyte, OPC, NasN, ctrl1 Micro 1000 cells 351 2 15. Subsetting a Seurat object based on colnames This can be misleading. Which language's style guidelines should be used when writing code that is supposed to be called from another language? So, I would like to merge the clusters together (using MergeSeurat option) and then recluster them to find overlap/distinctions between the clusters. By clicking Sign up for GitHub, you agree to our terms of service and This is what worked for me: Minimum number of cells to downsample to within sample.group. However, when I try to do any of the following: seurat_object <- subset (seurat_object, subset = meta . WhichCells : Identify cells matching certain criteria Can be used to downsample the data to a certain max per cell ident. The raw data can be found here. Arguments Value Returns a randomly subsetted seurat object Examples crazyhottommy/scclusteval documentation built on Aug. 5, 2021, 3:20 p.m. Have a question about this project? To subscribe to this RSS feed, copy and paste this URL into your RSS reader. Subsets a Seurat object containing Spatial Transcriptomics data while making sure that the images and the spot coordinates are subsetted correctly. Returns a list of cells that match a particular set of criteria such as This method expects "correspondences" or shared biological states among at least a subset of single cells across the groups. SubsetData : Return a subset of the Seurat object privacy statement. Well occasionally send you account related emails. Happy to hear that. It first does all the selection and potential inversion of cells, and then this is the bit concerning downsampling: So indeed, it groups it into the identity classes (e.g. What should I follow, if two altimeters show different altitudes? you may need to wrap feature names in backticks (``) if dashes If no cells are request, return a NULL; A stupid suggestion, but did you try to give it as a string ? **subset_deg **FindAllMarkers. I keep running out of RAM with my current pipeline, Bar Graph of Expression Data from Seurat Object. If no clustering was performed, and if the cells have the same orig.ident, only 1000 cells are sampled randomly independent of the clusters to which they will belong after computing FindClusters(). . You can see the code that is actually called as such: SeuratObject:::subset.Seurat, which in turn calls SeuratObject:::WhichCells.Seurat (as @yuhanH mentioned). But before downsampling, if you see KO cells are higher compared to WT cells. Setup the Seurat objects library ( Seurat) library ( SeuratData) library ( patchwork) library ( dplyr) library ( ggplot2) The dataset is available through our SeuratData package. I have two seurat objects, one with about 40k cells and another with around 20k cells. Setup the Seurat Object For this tutorial, we will be analyzing the a dataset of Peripheral Blood Mononuclear Cells (PBMC) freely available from 10X Genomics. There are 33 cells under the identity. See Also. [: 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 privacy statement. ctrl2 Micro 1000 cells Adding EV Charger (100A) in secondary panel (100A) fed off main (200A). My analysis is helped by the fact that the larger cluster is very homogeneous - so, random sampling of ~1000 cells is still very representative. You can however change the seed value and end up with a different dataset. I have a seurat object with 5 conditions and 9 cell types defined. Here is the slightly modified code I tried with the error: The error after the last line is: Connect and share knowledge within a single location that is structured and easy to search. You can check lines 714 to 716 in interaction.R. Identify blue/translucent jelly-like animal on beach. using FetchData, Low cutoff for the parameter (default is -Inf), High cutoff for the parameter (default is Inf), Returns all cells with the subset name equal to this value. How to subset the rows of my data frame based on a list of names? Seurat - Guided Clustering Tutorial Seurat - Satija Lab identity class, high/low values for particular PCs, ect.. But it didnt work.. Subsetting from seurat object based on orig.ident? There are 2,700 single cells that were sequenced on the Illumina NextSeq 500. Well occasionally send you account related emails. 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. Most functions now take an assay parameter, but you can set a Default Assay to avoid repetitive statements. Can be used to downsample the data to a certain ctrl1 Astro 1000 cells I ma just worried it is just picking the first 600 and not randomizing, https://www.rdocumentation.org/packages/base/versions/3.6.2/topics/sample. Returns a list of cells that match a particular set of criteria such as identity class, high/low values for particular PCs, ect.. # install dataset InstallData ("ifnb") Description Randomly subset (cells) seurat object by a rate Usage 1 RandomSubsetData (object, rate, random.subset.seed = NULL, .) WhichCells function - RDocumentation Find centralized, trusted content and collaborate around the technologies you use most. Here, the GEX = pbmc_small, for exemple. What is the symbol (which looks similar to an equals sign) called? Asking for help, clarification, or responding to other answers. Why did US v. Assange skip the court of appeal? Bioinformatics Stack Exchange is a question and answer site for researchers, developers, students, teachers, and end users interested in bioinformatics. The text was updated successfully, but these errors were encountered: Thank you Tim. Did the Golden Gate Bridge 'flatten' under the weight of 300,000 people in 1987? Inferring a single-cell trajectory is a machine learning problem. Factor to downsample data by. This is due to having ~100k cells in my starting object so I randomly sampled 60k or 50k with the SubsetData as I mentioned to use for the downstream analysis. If the null hypothesis is never really true, is there a point to using a statistical test without a priori power analysis? Here is my coding but it always shows. Default is all identities. By clicking Post Your Answer, you agree to our terms of service, privacy policy and cookie policy. I want to subset from my original seurat object (BC3) meta.data based on orig.ident. Sign in The text was updated successfully, but these errors were encountered: Hi, Downsample a seurat object, either globally or subset by a field Usage DownsampleSeurat(seuratObj, targetCells, subsetFields = NULL, seed = GetSeed()) Arguments. exp1 Micro 1000 cells RandomSubsetData: Randomly subset (cells) seurat object by a rate in downsample Maximum number of cells per identity class, default is Inf; downsampling will happen after all other operations, including inverting the cell selection seed Random seed for downsampling. I would like to randomly downsample the larger object to have the same number of cells as the smaller object, however I am getting an error when trying to subset. satijalab/seurat: vignettes/essential_commands.Rmd It won't necessarily pick the expected number of cells . If I have an input of 2000 cells and downsample to 500, how are te 1500 cells excluded? Sign up for a free GitHub account to open an issue and contact its maintainers and the community. Boolean algebra of the lattice of subspaces of a vector space? scanpy.pp.highly_variable_genes Scanpy 1.9.3 documentation Sign in - Logical expression indicating features/variables to keep, Extra parameters passed to WhichCells, such as slot, invert, or downsample. r - Conditional subsetting of Seurat object - Stack Overflow Why are players required to record the moves in World Championship Classical games? I want to create a subset of a cell expressing certain genes only. These genes can then be used for dimensional reduction on the original data including all cells. Number of cells to subsample. Subset a Seurat object RDocumentation. Related question: "SubsetData" cannot be directly used to randomly sample 1000 cells (let's say) from a larger object? But using a union of the variable genes might be even more robust. Downsample number of cells in Seurat object by specified factor. Seurat:::subset.Seurat (pbmc_small,idents="BC0") An object of class Seurat 230 features across 36 samples within 1 assay Active assay: RNA (230 features, 20 variable features) 2 dimensional reductions calculated: pca, tsne Share Improve this answer Follow answered Jul 22, 2020 at 15:36 StupidWolf 1,658 1 6 21 Add a comment Your Answer A package with high-level wrappers and pipelines for single-cell RNA-seq tools, Search the bimberlabinternal/CellMembrane package, bimberlabinternal/CellMembrane: A package with high-level wrappers and pipelines for single-cell RNA-seq tools, bimberlabinternal/CellMembrane documentation. SubsetSTData: Subset a Seurat object containing Staffli image data in For instance, you might do something like this: You signed in with another tab or window. inplace: bool (default: True) however, when i use subset(), it returns with Error. 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. Does it make sense to subsample as such even? to your account. The slice_sample() function in the dplyr package is useful here. Numeric [1,ncol(object)]. rev2023.5.1.43405. So, I am afraid that when I calculate varianble genes, the cluster with higher number of cells is going to be overrepresented. Introduction to SCTransform, v2 regularization Seurat - Satija Lab downsampled.obj <- large.obj[, sample(colnames(large.obj), size = ncol(small.obj), replace=F))]. Making statements based on opinion; back them up with references or personal experience. Parameter to subset on. This approach allows then to subset nicely, with more flexibility. However, for robustness issues, I would try to resample from obj1 several times using different seed values (which you can store for reproducibility), compute variable genes at each step as described above, and then get either the union or the intersection of those variable genes. rev2023.5.1.43405. Takes either a list of cells to use as a subset, or a parameter (for example, a gene), to subset on. 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? Downsample Seurat Description. The integration method that is available in the Seurat package utilizes the canonical correlation analysis (CCA). Already on GitHub? When do you use in the accusative case? Well occasionally send you account related emails. Using the same logic as @StupidWolf, I am getting the gene expression, then make a dataframe with two columns, and this information is directly added on the Seurat object. Hello All, 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). You signed in with another tab or window. data.table vs dplyr: can one do something well the other can't or does poorly? It only takes a minute to sign up. If a subsetField is provided, the string 'min' can also be used, in which case, If provided, data will be grouped by these fields, and up to targetCells will be retained per group. Why does Acts not mention the deaths of Peter and Paul? Sample UMI SampleUMI Seurat - Satija Lab 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. If you are going to use idents like that, make sure that you have told the software what your default ident category is. So, it's just a random selection. You can subset from the counts matrix, below I use pbmc_small dataset from the package, and I get cells that are CD14+ and CD14-: library (Seurat) CD14_expression = GetAssayData (object = pbmc_small, assay = "RNA", slot = "data") ["CD14",] This vector contains the counts for CD14 and also the names of the cells: head (CD14_expression,30 .