seurat subset downsample seurat subset downsample
I have a seurat object with 5 conditions and 9 cell types defined. 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 Sign in are kept in the output Seurat object which will make the STUtility functions Downsample single cell data Downsample number of cells in Seurat object by specified factor downsampleSeurat( object , subsample.factor = 1 , subsample.n = NULL , sample.group = NULL , min.group.size = 500 , seed = 1023 , verbose = T ) Arguments Value Seurat Object Author Nicholas Mikolajewicz Subset a Seurat object RDocumentation. How to refine signaling input into a handful of clusters out of many. Why are players required to record the moves in World Championship Classical games? Learn more about Stack Overflow the company, and our products. Thanks for the wonderful package. use.imputed=TRUE), Run the code above in your browser using DataCamp Workspace, WhichCells: Identify cells matching certain criteria, WhichCells(object, ident = NULL, ident.remove = NULL, cells.use = NULL, Description Randomly subset (cells) seurat object by a rate Usage 1 RandomSubsetData (object, rate, random.subset.seed = NULL, .) Folder's list view has different sized fonts in different folders. I want to create a subset of a cell expressing certain genes only. If anybody happens upon this in the future, there was a missing ')' in the above code. SubsetSTData: Subset a Seurat object containing Staffli image data in Can you tell me, when I use the downsample function, how does seurat exclude or choose cells? Creates a Seurat object containing only a subset of the cells in the original object. 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. If ident.use = NULL, then Seurat looks at your actual object@ident (see Seurat::WhichCells, l.6). Error in CellsByIdentities(object = object, cells = cells) : What is the symbol (which looks similar to an equals sign) called? scanpy.pp.highly_variable_genes Scanpy 1.9.3 documentation I would rather use the sample function directly. Seurat Methods Seurat-methods SeuratObject - GitHub Pages SubsetData function - RDocumentation I managed to reduce the vignette pbmc from the from 2700 to 600. **subset_deg **FindAllMarkers. Of course, your case does not exactly match theirs, since they have ~1.3M cells and, therefore, more chance to maximally enrich in rare cell types, and the tissues you're studying might be very different. Downsample a seurat object, either globally or subset by a field Usage DownsampleSeurat(seuratObj, targetCells, subsetFields = NULL, seed = GetSeed()) Arguments. Have a question about this project? Returns a list of cells that match a particular set of criteria such as identity class, high/low values for particular PCs, ect.. SampleUMI(data, max.umi = 1000, upsample = FALSE, verbose = FALSE) Arguments data Matrix with the raw count data max.umi Number of UMIs to sample to upsample Upsamples all cells with fewer than max.umi verbose Setup the Seurat objects library ( Seurat) library ( SeuratData) library ( patchwork) library ( dplyr) library ( ggplot2) The dataset is available through our SeuratData package. RDocumentation. So, I am afraid that when I calculate varianble genes, the cluster with higher number of cells is going to be overrepresented. SubsetData(object, cells.use = NULL, subset.name = NULL, ident.use = NULL, max.cells.per.ident. It won't necessarily pick the expected number of cells . Sign in Happy to hear that. It only takes a minute to sign up. If anybody happens upon this in the future, there was a missing ')' in the above code. If you use the default subset function there is a risk that images 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? rev2023.5.1.43405. Ubuntu won't accept my choice of password, Identify blue/translucent jelly-like animal on beach. ctrl2 Astro 1000 cells DEG. This is what worked for me: downsampled.obj <- large.obj[, sample(colnames(large.obj), size = ncol(small.obj), replace=F))]. 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. Did the Golden Gate Bridge 'flatten' under the weight of 300,000 people in 1987? Why are players required to record the moves in World Championship Classical games? inplace: bool (default: True) If I always end up with the same mean and median (UMI) then is it truly random sampling? Default is INF. I think this is basically what you did, but I think this looks a little nicer. If you make a dataframe containing the barcodes, conditions, and celltypes, you can sample 1000 cells within each condition/ celltype. This is what worked for me: privacy statement. Try doing that, and see for yourself if the mean or the median remain the same. I have two seurat objects, one with about 40k cells and another with around 20k cells. Also, please provide a reproducible example data for testing, dput (myData). Well occasionally send you account related emails. 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. 5 comments williamsdrake commented on Jun 4, 2020 edited Hi Seurat Team, Error in CellsByIdentities (object = object, cells = cells) : timoast closed this as completed on Jun 5, 2020 ShellyCoder mentioned this issue 351 2 15. Subsetting a Seurat object based on colnames 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). 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-: This vector contains the counts for CD14 and also the names of the cells: Getting the ids can be done using which : A bit dumb, but I guess this is one way to check whether it works: I am using this code to actually add the information directly on the meta.data. Subsets a Seurat object containing Spatial Transcriptomics data while 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! Here is the slightly modified code I tried with the error: The error after the last line is: The slice_sample() function in the dplyr package is useful here. Which language's style guidelines should be used when writing code that is supposed to be called from another language? Thanks for contributing an answer to Stack Overflow! They actually both fail due to syntax errors, yours included @williamsdrake . Boolean algebra of the lattice of subspaces of a vector space? . Developed by Rahul Satija, Andrew Butler, Paul Hoffman, Tim Stuart. Eg, the name of a gene, PC1, a For example, Thanks for this, but I really want to understand more how the downsample function actualy works. Seurat Tutorial - 65k PBMCs - Parse Biosciences Have a question about this project? Cell types: Micro, Astro, Oligo, Endo, InN, ExN, Pericyte, OPC, NasN, ctrl1 Micro 1000 cells 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. Making statements based on opinion; back them up with references or personal experience. 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. I want to subset from my original seurat object (BC3) meta.data based on orig.ident. Hi subset: bool (default: False) Inplace subset to highly-variable genes if True otherwise merely indicate highly variable genes. This subset also has the same exact mean and median as my original object Im subsetting from. # 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, as.Seurat: Coerce to a 'Seurat' Object; as.sparse: Cast to Sparse; AttachDeps: . the Allied commanders were appalled to learn that 300 glider troops had drowned at sea. To learn more, see our tips on writing great answers. Can be used to downsample the data to a certain If NULL, does not set a seed. random.seed Random seed for downsampling Value Returns a Seurat object containing only the relevant subset of cells Examples Run this code # NOT RUN { pbmc1 <- SubsetData (object = pbmc_small, cells = colnames (x = pbmc_small) [1:40]) pbmc1 # } # NOT RUN { # } Identity classes to subset. 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. What do hollow blue circles with a dot mean on the World Map? Hi, I guess you can randomly sample your cells from that cluster using sample() (from the base in R). Seurat (version 2.3.4) making sure that the images and the spot coordinates are subsetted correctly. 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. Seurat Command List Seurat - Satija Lab Examples ## Not run: # Subset using meta data to keep spots with more than 1000 unique genes se.subset <- SubsetSTData(se, expression = nFeature_RNA >= 1000) # Subset by a . Meta data grouping variable in which min.group.size will be enforced. column name in object@meta.data, etc. By clicking Sign up for GitHub, you agree to our terms of service and max per cell ident. Data visualization methods in Seurat Seurat - Satija Lab Single-cell RNA-seq: Integration For this application, using SubsetData is fine, it seems from your answers. Subset of cell names. Example See Also. Default is all identities. Parameter to subset on. Randomly downsample seurat object #3108 - Github My question is Is this randomized ? 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. 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. So if you repeat your subsetting several times with the same max.cells.per.ident, you will always end up having the same cells. You signed in with another tab or window. Asking for help, clarification, or responding to other answers. You can check lines 714 to 716 in interaction.R. Already on GitHub? So, it's just a random selection. You can see the code that is actually called as such: SeuratObject:::subset.Seurat, which in turn calls SeuratObject:::WhichCells.Seurat (as @yuhanH mentioned). How to force Unity Editor/TestRunner to run at full speed when in background? There are 33 cells under the identity. 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. If a subsetField is provided, the string 'min' can also be . By clicking Accept all cookies, you agree Stack Exchange can store cookies on your device and disclose information in accordance with our Cookie Policy. privacy statement. The first step is to select the genes Monocle will use as input for its machine learning approach. 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. you may need to wrap feature names in backticks (``) if dashes Use MathJax to format equations. If NULL, does not set a seed Value A vector of cell names See also FetchData Examples For instance, you might do something like this: You signed in with another tab or window. For ex., 50k or 60k. Cannot find cells provided, Any help or guidance would be appreciated. Sign in Well occasionally send you account related emails. 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. Includes an option to upsample cells below specified UMI as well. Usage 1 2 3 To learn more, see our tips on writing great answers. To subscribe to this RSS feed, copy and paste this URL into your RSS reader. ctrl3 Astro 1000 cells Seurat has four tests for differential expression which can be set with the test.use parameter: ROC test ("roc"), t-test ("t"), LRT test based on zero-inflated data ("bimod", default), LRT test based on tobit-censoring models ("tobit") The ROC test returns the 'classification power' for any individual marker (ranging from 0 - random, to 1 - Two MacBook Pro with same model number (A1286) but different year. @del2007: What you showed as an example allows you to sample randomly a maximum of 1000 cells from each cluster who's information is stored in object@ident. seuratObj: The seurat object. 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. Is it safe to publish research papers in cooperation with Russian academics? Subsetting from seurat object based on orig.ident? So, I would like to merge the clusters together (using MergeSeurat option) and then recluster them to find overlap/distinctions between the clusters. Additional arguments to be passed to FetchData (for example, DownsampleSeurat: Downsample Seurat in bimberlabinternal/CellMembrane downsample: Maximum number of cells per identity class, default is Inf; downsampling will happen after all other operations, . WhichCells : Identify cells matching certain criteria Sign up for a free GitHub account to open an issue and contact its maintainers and the community. 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. The steps in the Seurat integration workflow are outlined in the figure below: Downsample single cell data downsampleSeurat scMiko exp2 Micro 1000 cells Thanks again for any help! Can you still use Commanders Strike if the only attack available to forego is an attack against an ally? Seurat (version 3.1.4) Description. Creates a Seurat object containing only a subset of the cells in the original object. satijalab/seurat: vignettes/essential_commands.Rmd By clicking Post Your Answer, you agree to our terms of service, privacy policy and cookie policy. Have a question about this project? Conditions: ctrl1, ctrl2, ctrl3, exp1, exp2 We start by reading in the data. exp1 Micro 1000 cells Identify blue/translucent jelly-like animal on beach. The raw data can be found here. If the null hypothesis is never really true, is there a point to using a statistical test without a priori power analysis? Yes it does randomly sample (using the sample() function from base). identity class, high/low values for particular PCs, ect.. 4 comments chrismahony commented on May 19, 2020 Collaborator yuhanH closed this as completed on May 22, 2020 evanbiederstedt mentioned this issue on Dec 23, 2021 Downsample from each cluster kharchenkolab/conos#115 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. It's a closed issue, but I stumbled across the same question as well, and went on to find the answer. For more information on customizing the embed code, read Embedding Snippets. 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). 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. 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. 1. by default, throws an error, A predicate expression for feature/variable expression, Factor to downsample data by. crash. Connect and share knowledge within a single location that is structured and easy to search. I followed the example in #243, however this issue used a previous version of Seurat and the code didn't work as-is. - zx8754. In other words - is there a way to randomly subscluster my cells in an unsupervised manner? Thank you for the suggestion. ctrl1 Astro 1000 cells Why does Acts not mention the deaths of Peter and Paul? Can be used to downsample the data to a certain max per cell ident. Sign up for a free GitHub account to open an issue and contact its maintainers and the community. How are engines numbered on Starship and Super Heavy? I keep running out of RAM with my current pipeline, Bar Graph of Expression Data from Seurat Object. Here we present an example analysis of 65k peripheral blood mononuclear blood cells (PBMCs) using the R package Seurat. If specified, overides subsample.factor. Great. Heatmap of gene subset from microarray expression data in R. How to filter genes from seuratobject in slotname @data? Hi Leon, FilterCells function - RDocumentation Thank you. Does it not? Well occasionally send you account related emails. WhichCells function - RDocumentation Random picking of cells from an object #243 - Github They actually both fail due to syntax errors, yours included @williamsdrake . Downsample number of cells in Seurat object by specified factor. What pareameters are excluding these cells? Numeric [1,ncol(object)]. Already on GitHub? Was Aristarchus the first to propose heliocentrism? Well occasionally send you account related emails. By clicking Accept all cookies, you agree Stack Exchange can store cookies on your device and disclose information in accordance with our Cookie Policy. Already on GitHub? exp2 Astro 1000 cells. However, when I try to do any of the following: seurat_object <- subset (seurat_object, subset = meta . Character. 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. For the dispersion based methods in their default workflows, Seurat passes the cutoffs whereas Cell Ranger passes n_top_genes. Number of cells to subsample. rev2023.5.1.43405. Short story about swapping bodies as a job; the person who hires the main character misuses his body. The integration method that is available in the Seurat package utilizes the canonical correlation analysis (CCA). If there are insufficient cells to achieve the target min.group.size, only the available cells are retained. Content Discovery initiative April 13 update: Related questions using a Review our technical responses for the 2023 Developer Survey, Filter data.frame rows by a logical condition, How to make a great R reproducible example, Subset data to contain only columns whose names match a condition. how to make a subset of cells expressing certain gene in seurat R You can set invert = TRUE, then it will exclude input cells. Sign up for a free GitHub account to open an issue and contact its maintainers and the community. Image of minimal degree representation of quasisimple group unique up to conjugacy, Folder's list view has different sized fonts in different folders. However, you have to know that for reproducibility, a random seed is set (in this case random.seed = 1). targetCells: The desired cell number to retain per unit of data. You signed in with another tab or window. CCA-Seurat. Indentity classes to remove. Sample UMI SampleUMI Seurat - Satija Lab Adding EV Charger (100A) in secondary panel (100A) fed off main (200A). 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. Here, the GEX = pbmc_small, for exemple. I would like to randomly downsample each cell type for each condition. Choose the flavor for identifying highly variable genes. however, when i use subset(), it returns with Error. There are 2,700 single cells that were sequenced on the Illumina NextSeq 500. By clicking Sign up for GitHub, you agree to our terms of service and Site design / logo 2023 Stack Exchange Inc; user contributions licensed under CC BY-SA. What are the advantages of running a power tool on 240 V vs 120 V? Identify cells matching certain criteria WhichCells These genes can then be used for dimensional reduction on the original data including all cells. 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