seurat subset downsample

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. If no cells are request, return a NULL; Numeric [1,ncol(object)]. I want to subset from my original seurat object (BC3) meta.data based on orig.ident. By clicking Accept all cookies, you agree Stack Exchange can store cookies on your device and disclose information in accordance with our 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. Why don't we use the 7805 for car phone chargers? rev2023.5.1.43405. They actually both fail due to syntax errors, yours included @williamsdrake . How to subset the rows of my data frame based on a list of names? 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. = 1000). By clicking Sign up for GitHub, you agree to our terms of service and But using a union of the variable genes might be even more robust. Asking for help, clarification, or responding to other answers. By clicking Sign up for GitHub, you agree to our terms of service and Numeric [0,1]. 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. Asking for help, clarification, or responding to other answers. By clicking Accept all cookies, you agree Stack Exchange can store cookies on your device and disclose information in accordance with our Cookie Policy. Seurat (version 3.1.4) Description. Usage Arguments., Value. What is the symbol (which looks similar to an equals sign) called? exp2 Micro 1000 cells between numbers are present in the feature name, Maximum number of cells per identity class, default is Bioinformatics Stack Exchange is a question and answer site for researchers, developers, students, teachers, and end users interested in bioinformatics. Parameter to subset on. targetCells: The desired cell number to retain per unit of data. Hi This subset also has the same exact mean and median as my original object Im subsetting from. Site design / logo 2023 Stack Exchange Inc; user contributions licensed under CC BY-SA. Well occasionally send you account related emails. The raw data can be found here. DEG. For your last question, I suggest you read this bioRxiv paper. Sign up for a free GitHub account to open an issue and contact its maintainers and the community. This can be misleading. Two MacBook Pro with same model number (A1286) but different year. We start by reading in the data. If ident.use = NULL, then Seurat looks at your actual object@ident (see Seurat::WhichCells, l.6). 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. What do hollow blue circles with a dot mean on the World Map? Well occasionally send you account related emails. To learn more, see our tips on writing great answers. I managed to reduce the vignette pbmc from the from 2700 to 600. These genes can then be used for dimensional reduction on the original data including all cells. By clicking Sign up for GitHub, you agree to our terms of service and downsampled.obj <- large.obj[, sample(colnames(large.obj), size = ncol(small.obj), replace=F))]. exp1 Astro 1000 cells Thanks again for any help! Inferring a single-cell trajectory is a machine learning problem. Did the Golden Gate Bridge 'flatten' under the weight of 300,000 people in 1987? Sign up for a free GitHub account to open an issue and contact its maintainers and the community. as.Seurat: Coerce to a 'Seurat' Object; as.sparse: Cast to Sparse; AttachDeps: . Have a question about this project? These genes can then be used for dimensional reduction on the original data including all cells. For ex., 50k or 60k. Usage 1 2 3 The number of column it is reduced ( so the object). 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. Happy to hear that. If you use the default subset function there is a risk that images Are there any canonical examples of the Prime Directive being broken that aren't shown on screen? MathJax reference. which command here is leading to randomization ? My question is Is this randomized ? . 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? @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. Returns a list of cells that match a particular set of criteria such as identity class, high/low values for particular PCs, ect.. But this is something you can test by minimally subsetting your data (i.e. Heatmap of gene subset from microarray expression data in R. How to filter genes from seuratobject in slotname @data? Identity classes to subset. Examples Run this code # NOT . 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 you are going to use idents like that, make sure that you have told the software what your default ident category is. 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. It won't necessarily pick the expected number of cells . 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. Ubuntu won't accept my choice of password, Identify blue/translucent jelly-like animal on beach. It's a closed issue, but I stumbled across the same question as well, and went on to find the answer. Yep! Already on GitHub? By clicking Sign up for GitHub, you agree to our terms of service and Cell types: Micro, Astro, Oligo, Endo, InN, ExN, Pericyte, OPC, NasN, ctrl1 Micro 1000 cells 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. By clicking Post Your Answer, you agree to our terms of service, privacy policy and cookie policy. I followed the example in #243, however this issue used a previous version of Seurat and the code didn't work as-is. downsample: Maximum number of cells per identity class, default is Inf; downsampling will happen after all other operations, . If NULL, does not set a seed Value A vector of cell names See also FetchData Examples If specified, overides subsample.factor. subset_deg <- function(obj . 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. What are the advantages of running a power tool on 240 V vs 120 V? invert, or downsample. I checked the active.ident to make sure the identity has not shifted to any other column, but still I am getting the error? 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 Returns a list of cells that match a particular set of criteria such as Seurat (version 2.3.4) 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. 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 Already on GitHub? making sure that the images and the spot coordinates are subsetted correctly. Did the drapes in old theatres actually say "ASBESTOS" on them? To subscribe to this RSS feed, copy and paste this URL into your RSS reader. 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. 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. Why are players required to record the moves in World Championship Classical games? Again, Id like to confirm that it randomly samples! But it didnt work.. Subsetting from seurat object based on orig.ident? to your account. Was Aristarchus the first to propose heliocentrism? expression: . If this new subset is not randomly sampled, then on what criteria is it sampled? Interpreting non-statistically significant results: Do we have "no evidence" or "insufficient evidence" to reject the null? Can be used to downsample the data to a certain max per cell ident. Adding EV Charger (100A) in secondary panel (100A) fed off main (200A). Identify blue/translucent jelly-like animal on beach. Other option is to get the cell names of that ident and then pass a vector of cell names. 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. Learn more about Stack Overflow the company, and our products. 1. to your account. are kept in the output Seurat object which will make the STUtility functions For the dispersion based methods in their default workflows, Seurat passes the cutoffs whereas Cell Ranger passes n_top_genes. Does it make sense to subsample as such even? For more information on customizing the embed code, read Embedding Snippets. Downsample each cell to a specified number of UMIs. Creates a Seurat object containing only a subset of the cells in the original object. to your account. Adding EV Charger (100A) in secondary panel (100A) fed off main (200A). Additional arguments to be passed to FetchData (for example, 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. SubsetData(object, cells.use = NULL, subset.name = NULL, ident.use = NULL, max.cells.per.ident. How to refine signaling input into a handful of clusters out of many. Downsample number of cells in Seurat object by specified factor. For more information on customizing the embed code, read Embedding Snippets. 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") data.table vs dplyr: can one do something well the other can't or does poorly? You can check lines 714 to 716 in interaction.R. just "BC03" ? 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). Step 1: choosing genes that define progress. 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. If I always end up with the same mean and median (UMI) then is it truly random sampling? 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. What should I follow, if two altimeters show different altitudes? subset.name = NULL, accept.low = -Inf, accept.high = Inf, 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 Eg, the name of a gene, PC1, a exp1 Micro 1000 cells However, you have to know that for reproducibility, a random seed is set (in this case random.seed = 1). Selecting cluster resolution using specificity criterion, Marker-based cell-type annotation using Miko Scoring, Gene program discovery using SSN analysis.
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