Parameter to subset on. 1. can evaluate anything that can be pulled by FetchData; please note, 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 . Are there any canonical examples of the Prime Directive being broken that aren't shown on screen? identity class, high/low values for particular PCs, etc. If NULL, does not set a seed Value A vector of cell names See also FetchData Examples Sign in Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community. This works for me, with the metadata column being called "group", and "endo" being one possible group there. By clicking Post Your Answer, you agree to our terms of service, privacy policy and cookie policy. Well occasionally send you account related emails. to your account. But before downsampling, if you see KO cells are higher compared to WT cells. I followed the example in #243, however this issue used a previous version of Seurat and the code didn't work as-is. By clicking Post Your Answer, you agree to our terms of service, privacy policy and cookie policy. 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. Factor to downsample data by. 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. Subset of cell names. 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. Returns a list of cells that match a particular set of criteria such as identity class, high/low values for particular PCs, ect.. My analysis is helped by the fact that the larger cluster is very homogeneous - so, random sampling of ~1000 cells is still very representative. Usage 1 2 3 Downsample a seurat object, either globally or subset by a field Usage DownsampleSeurat(seuratObj, targetCells, subsetFields = NULL, seed = GetSeed()) Arguments. 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. New blog post from our CEO Prashanth: Community is the future of AI, Improving the copy in the close modal and post notices - 2023 edition, Subsetting of object existing of two samples, Set new Idents based on gene expression in Seurat and mix n match identities to compare using FindAllMarkers, What column and row naming requirements exist with Seurat (context: when loading SPLiT-Seq data), Subsetting a Seurat object based on colnames, How to manage memory contraints when analyzing a large number of gene count matrices? [: 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 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. 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(). I dont have much choice, its either that or my R crashes with so many cells. 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. exp1 Micro 1000 cells which command here is leading to randomization ? 351 2 15. The raw data can be found here. **subset_deg **FindAllMarkers. This approach allows then to subset nicely, with more flexibility. It only takes a minute to sign up. Did the Golden Gate Bridge 'flatten' under the weight of 300,000 people in 1987? Great. There are 33 cells under the identity. Sign in Hi Thank you. Learn more about Stack Overflow the company, and our products. 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. Cell types: Micro, Astro, Oligo, Endo, InN, ExN, Pericyte, OPC, NasN, ctrl1 Micro 1000 cells What should I follow, if two altimeters show different altitudes? So if you repeat your subsetting several times with the same max.cells.per.ident, you will always end up having the same cells. The best answers are voted up and rise to the top, Not the answer you're looking for? So, I am afraid that when I calculate varianble genes, the cluster with higher number of cells is going to be overrepresented. 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. However, one of the clusters has ~10-fold more number of cells than the other one. 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 . Which language's style guidelines should be used when writing code that is supposed to be called from another language? Any argument that can be retreived 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. Well occasionally send you account related emails. 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). subset.name = NULL, accept.low = -Inf, accept.high = Inf, Meta data grouping variable in which min.group.size will be enforced. Short story about swapping bodies as a job; the person who hires the main character misuses his body. Sign in to comment Assignees No one assigned Labels None yet Projects None yet Milestone Asking for help, clarification, or responding to other answers. Step 1: choosing genes that define progress. The slice_sample() function in the dplyr package is useful here. Which ability is most related to insanity: Wisdom, Charisma, Constitution, or Intelligence? to your account. ctrl3 Micro 1000 cells Numeric [0,1]. Examples Run this code # NOT . 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. Numeric [1,ncol(object)]. Have a question about this project? 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 in If anybody happens upon this in the future, there was a missing ')' in the above code. 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 Why are players required to record the moves in World Championship Classical games? Why does Acts not mention the deaths of Peter and Paul? Already on GitHub? Find centralized, trusted content and collaborate around the technologies you use most. 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. seuratObj: The seurat object. targetCells: The desired cell number to retain per unit of data. You signed in with another tab or window. Already on GitHub? Why the obscure but specific description of Jane Doe II in the original complaint for Westenbroek v. Kappa Kappa Gamma Fraternity? 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. inverting the cell selection, Random seed for downsampling. For example, Thanks for this, but I really want to understand more how the downsample function actualy works. Error in CellsByIdentities(object = object, cells = cells) : These genes can then be used for dimensional reduction on the original data including all cells. 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. This subset also has the same exact mean and median as my original object Im subsetting from. The number of column it is reduced ( so the object). column name in object@meta.data, etc. Identify blue/translucent jelly-like animal on beach. To learn more, see our tips on writing great answers. Indentity classes to remove. by default, throws an error, A predicate expression for feature/variable expression, If I verify the subsetted object, it does have the nr of cells I asked for in max.cells.per.ident (only one ident in one starting object). privacy statement. 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). 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. you may need to wrap feature names in backticks (``) if dashes When do you use in the accusative case? Other option is to get the cell names of that ident and then pass a vector of cell names. For your last question, I suggest you read this bioRxiv paper. If specified, overides subsample.factor. Thanks for the answer! In other words - is there a way to randomly subscluster my cells in an unsupervised manner? 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 . See Also. Here we present an example analysis of 65k peripheral blood mononuclear blood cells (PBMCs) using the R package Seurat. Takes either a list of cells to use as a subset, or a parameter (for example, a gene), to subset on. Seurat (version 3.1.4) Description. Default is INF. Creates a Seurat object containing only a subset of the cells in the original object. The integration method that is available in the Seurat package utilizes the canonical correlation analysis (CCA). making sure that the images and the spot coordinates are subsetted correctly. Sign up for a free GitHub account to open an issue and contact its maintainers and the community. The first step is to select the genes Monocle will use as input for its machine learning approach. Can you tell me, when I use the downsample function, how does seurat exclude or choose cells? Subsets a Seurat object containing Spatial Transcriptomics data while @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. Connect and share knowledge within a single location that is structured and easy to search. exp2 Micro 1000 cells Sign in If you make a dataframe containing the barcodes, conditions, and celltypes, you can sample 1000 cells within each condition/ celltype. Takes either a list of cells to use as a subset, or a parameter (for example, a gene), to subset on. I managed to reduce the vignette pbmc from the from 2700 to 600. Choose the flavor for identifying highly variable genes. By clicking Accept all cookies, you agree Stack Exchange can store cookies on your device and disclose information in accordance with our Cookie Policy. The code could only make sense if the data is a square, equal number of rows and columns. If NULL, does not set a seed. # install dataset InstallData ("ifnb") privacy statement. identity class, high/low values for particular PCs, ect.. Not the answer you're looking for? Browse other questions tagged, Start here for a quick overview of the site, Detailed answers to any questions you might have, Discuss the workings and policies of this site. accept.value = NULL, max.cells.per.ident = Inf, random.seed = 1, ). What are the advantages of running a power tool on 240 V vs 120 V? Boolean algebra of the lattice of subspaces of a vector space? . The text was updated successfully, but these errors were encountered: Thank you Tim. the Allied commanders were appalled to learn that 300 glider troops had drowned at sea. 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. Includes an option to upsample cells below specified UMI as well. Thanks again for any help! Making statements based on opinion; back them up with references or personal experience. Default is NULL. Can be used to downsample the data to a certain max per cell ident. 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. to your account. Two MacBook Pro with same model number (A1286) but different year. 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 Thank you for the suggestion. subset_deg <- function(obj . 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. Adding EV Charger (100A) in secondary panel (100A) fed off main (200A). This method expects "correspondences" or shared biological states among at least a subset of single cells across the groups. You can set invert = TRUE, then it will exclude input cells. Try doing that, and see for yourself if the mean or the median remain the same. If a subsetField is provided, the string 'min' can also be . You can however change the seed value and end up with a different dataset. Can be used to downsample the data to a certain For this application, using SubsetData is fine, it seems from your answers. 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. 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. rev2023.5.1.43405. 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. to your account. If I always end up with the same mean and median (UMI) then is it truly random sampling? ctrl3 Astro 1000 cells To subscribe to this RSS feed, copy and paste this URL into your RSS reader. How to force Unity Editor/TestRunner to run at full speed when in background? 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. I have two seurat objects, one with about 40k cells and another with around 20k cells. Otherwise, if you'd like to have equal number of cells (optimally) per cluster in your final dataset after subsetting, then what you proposed would do the job. Identity classes to subset. Why don't we use the 7805 for car phone chargers? however, when i use subset(), it returns with Error. Is it safe to publish research papers in cooperation with Russian academics? ctrl2 Astro 1000 cells crash. = 1000). If this new subset is not randomly sampled, then on what criteria is it sampled? Minimum number of cells to downsample to within sample.group. Inf; downsampling will happen after all other operations, including Subset a Seurat object RDocumentation. If there are insufficient cells to achieve the target min.group.size, only the available cells are retained. 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. Therefore I wanted to confirm: does the SubsetData blindly randomly sample? Interpreting non-statistically significant results: Do we have "no evidence" or "insufficient evidence" to reject the null? Downsample number of cells in Seurat object by specified factor. Yes it does randomly sample (using the sample() function from base). The steps in the Seurat integration workflow are outlined in the figure below: If you are going to use idents like that, make sure that you have told the software what your default ident category is. just "BC03" ? Why did US v. Assange skip the court of appeal? 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? If the null hypothesis is never really true, is there a point to using a statistical test without a priori power analysis? Downsample a seurat object, either globally or subset by a field, The desired cell number to retain per unit of data. Is a downhill scooter lighter than a downhill MTB with same performance? ctrl1 Astro 1000 cells I would rather use the sample function directly. Example Happy to hear that. Here is the slightly modified code I tried with the error: The error after the last line is: If I have an input of 2000 cells and downsample to 500, how are te 1500 cells excluded? You signed in with another tab or window. MathJax reference. Inferring a single-cell trajectory is a machine learning problem. subset: bool (default: False) Inplace subset to highly-variable genes if True otherwise merely indicate highly variable genes. Making statements based on opinion; back them up with references or personal experience. I have a seurat object with 5 conditions and 9 cell types defined. You can check lines 714 to 716 in interaction.R. Ubuntu won't accept my choice of password, Identify blue/translucent jelly-like animal on beach. What pareameters are excluding these cells? Thanks for contributing an answer to Stack Overflow! SubsetData(object, cells.use = NULL, subset.name = NULL, ident.use = NULL, max.cells.per.ident. What is the symbol (which looks similar to an equals sign) called? Default is INF. Hello All, It's a closed issue, but I stumbled across the same question as well, and went on to find the answer. privacy statement. This is pretty much what Jean-Baptiste was pointing out. Setup the Seurat objects library ( Seurat) library ( SeuratData) library ( patchwork) library ( dplyr) library ( ggplot2) The dataset is available through our SeuratData package. Site design / logo 2023 Stack Exchange Inc; user contributions licensed under CC BY-SA. 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 - We start by reading in the data. Number of cells to subsample. Have a question about this project? Site design / logo 2023 Stack Exchange Inc; user contributions licensed under CC BY-SA. # 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, Numeric [1,ncol(object)]. For ex., 50k or 60k. So if you want to sample randomly 1000 cells, independent of the clusters to which those cells belong, you can simply provide a vector of cell names to the cells.use argument. 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! Downsample Seurat Description. Appreciate the detailed code you wrote. Did the drapes in old theatres actually say "ASBESTOS" on them? So, I would like to merge the clusters together (using MergeSeurat option) and then recluster them to find overlap/distinctions between the clusters. Sign up for a free GitHub account to open an issue and contact its maintainers and the community. What do hollow blue circles with a dot mean on the World Map? Selecting cluster resolution using specificity criterion, Marker-based cell-type annotation using Miko Scoring, Gene program discovery using SSN analysis. Character. 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. These genes can then be used for dimensional reduction on the original data including all cells. 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? A stupid suggestion, but did you try to give it as a string ? - zx8754. Hi Leon, This can be misleading. 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. By clicking Sign up for GitHub, you agree to our terms of service and between numbers are present in the feature name, Maximum number of cells per identity class, default is Does it not? Generating points along line with specifying the origin of point generation in QGIS. Already on GitHub? 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. By clicking Sign up for GitHub, you agree to our terms of service and Most functions now take an assay parameter, but you can set a Default Assay to avoid repetitive statements. I want to create a subset of a cell expressing certain genes only. I would like to randomly downsample each cell type for each condition. They actually both fail due to syntax errors, yours included @williamsdrake . If anybody happens upon this in the future, there was a missing ')' in the above code. Here is my coding but it always shows. 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 Learn R. Search all packages and functions. downsampled.obj <- large.obj[, sample(colnames(large.obj), size = ncol(small.obj), replace=F))]. Cannot find cells provided, Any help or guidance would be appreciated. Also, please provide a reproducible example data for testing, dput (myData). Additional arguments to be passed to FetchData (for example, However, when I try to do any of the following: seurat_object <- subset (seurat_object, subset = meta . Image of minimal degree representation of quasisimple group unique up to conjugacy, Folder's list view has different sized fonts in different folders. Description Randomly subset (cells) seurat object by a rate Usage 1 RandomSubsetData (object, rate, random.subset.seed = NULL, .) Default is all identities. 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. There are 2,700 single cells that were sequenced on the Illumina NextSeq 500. 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. DoHeatmap ( subset (pbmc3k.final, downsample = 100), features = features, size = 3) New additions to FeaturePlot FeaturePlot (pbmc3k.final, features = "MS4A1") FeaturePlot (pbmc3k.final, features = "MS4A1", min.cutoff = 1, max.cutoff = 3) FeaturePlot (pbmc3k.final, features = c ("MS4A1", "PTPRCAP"), min.cutoff = "q10", max.cutoff = "q90") Does it make sense to subsample as such even? Subsets a Seurat object containing Spatial Transcriptomics data while making sure that the images and the spot coordinates are subsetted correctly. Usage Arguments., Value. Eg, the name of a gene, PC1, a Again, Id like to confirm that it randomly samples! You signed in with another tab or window. Learn R. Search all packages and functions. 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. Have a question about this project? exp1 Astro 1000 cells How to refine signaling input into a handful of clusters out of many. max per cell ident. If the null hypothesis is never really true, is there a point to using a statistical test without a priori power analysis? Yep! How to subset the rows of my data frame based on a list of names? Should I re-do this cinched PEX connection? as.Seurat: Coerce to a 'Seurat' Object; as.sparse: Cast to Sparse; AttachDeps: . Seurat (version 2.3.4) Hi, I guess you can randomly sample your cells from that cluster using sample() (from the base in R). I want to subset from my original seurat object (BC3) meta.data based on orig.ident.
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