seurat subset multiple conditions
Dodane 10 maja 2023IFN induces epigenetic programming of human T-bethi B cells and promotes TLR7/8 and IL-21 induced differentiation. I tried. For f and g, statistical analysis of the gene set enrichment and variation analyses was performed as outlined in Methods, and all adjusted P values are shown. To subscribe to this RSS feed, copy and paste this URL into your RSS reader. max.cells.per.ident = Inf, USA 104, 97709775 (2007). Black lines indicate trajectory. Here, we take the average expression of both the stimulated and control naive T cells and CD14 monocyte populations and generate the scatter plots, highlighting genes that exhibit dramatic responses to interferon stimulation. @vertesy just came here to chime in after seeing your comment mate, so I tried what you are suggesting, and I see no marked difference, in fact, I don't have the data to show rn because I've a lot on my plate currently, but subset>integrate>re-cluster is more laborious and less useful than integrate>subset>re-cluster. In addition, reconstruction of clonal lineage trees and visualizing persistent S+ Bm cell clones in a circos plot indicated that individual Bm cell clones acquired different Bm cell fates; for example, a given clone was of a CD21+CD27 resting phenotype at month 6 and adopted CD21+CD27+ resting, CD21CD27+CD71+ or CD21CD27FcRL5+ Bm cell phenotype at month 12 post-infection (post-vaccination) (Fig. Niessl, J. et al. ## [82] stringr_1.5.0 fastmap_1.1.1 yaml_2.3.7 212, 20412056 (2015). These authors contributed equally: Yves Zurbuchen, Jan Michler. If they had a confirmed SARS-CoV-2 infection and/or SARS-CoV-2 nucleocapsid-specific antibodies, they were considered SARS-CoV-2-recovered. I have a conceptual question about the batch-correction (integration) model developed by Seurat (the one from the most recent vignette for integration with SCTransform - Compiled: 2019-07-16). We probed the Bm cell response to antigen reexposure in 35 of the 65 patients with COVID-19 who had received mRNA vaccination between month 6 and month 12 post-infection (Extended Data Fig. Percentages indicate frequencies of clonally expanded cells. Subsequent reclustering of Bm cells resolved six clusters (Fig. ## [121] R6_2.5.1 promises_1.2.0.1 KernSmooth_2.23-20 and the Botnar Research Centre for Child Health (COVID-19 FTC to A.E.M.). a, WNNUMAP was derived from scRNA-seq dataset at months 6 and 12 post-infection (n=9) and colored by indicated Bm cell subsets (top) and S+ and S separated by month 6 preVac, month 12 nonVac and month 12 postVac (bottom). Are there any canonical examples of the Prime Directive being broken that aren't shown on screen? ## [7] splines_4.2.0 listenv_0.9.0 scattermore_0.8 The joint analysis of two or more single-cell datasets poses unique challenges. I have been following the SCTransform integration tutorial and it doesn't mention how to FindClusters or identify cluster specific markers. 3 Identification of SARS-CoV-2 S, Extended Data Fig. PubMed So there is really no simple answer because heterogeneous populations themselves should be reproducibly present in multiple individuals, in order to identify that cell type as an organism-specific cell not a donor-specific transcriptional fluctuation in a particular cell population. Immunol. Thanks for contributing an answer to Bioinformatics Stack Exchange! The S+ Bm cell subset distribution of newly detected clones (n=1,357 clones) at month 12 post-infection (post-vaccination) was comparable to the persistent clones (Fig. 8e,f). An AUC value of 1 means that expression values for this gene alone can perfectly classify the two groupings (i.e. Shared transcriptional profiles of atypical B cells suggest common drivers of expansion and function in malaria, HIV, and autoimmunity. 9b). c, Pie chart show the percentage of SWT binders that also bind RBD in scRNA-seq dataset. ## [1] cowplot_1.1.1 ggplot2_3.4.1 Best wishes e, SHM counts of S+ Bm cells were derived at preVac (n=634 cells), month 12 nonvaccinated (nonVac; n=197 cells), and early (less than 24days; n=838 cell) and late (more than 84days; n=1,116 cells) postVac. Looking for job perks? Asking for help, clarification, or responding to other answers. Also, instead of changing the default assay to "RNA", finding the variable features, and changing the default assay back to "integrated", would it be make more sense to just delete those lines of code and just change: Dominguez, C. X. et al. Wang, Z. et al. Downstream analysis was conducted in R version 4.1.0 mainly with the package Seurat (v4.1.1) (ref. 25,26,27,28,29). 2b). How to convert a sequence of integers into a monomial. 10, eaan8405 (2018). ## [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C Altogether, these observations indicated that antigen reexposure by SARS-CoV-2 vaccination of SARS-CoV-2-recovered and SARS-CoV-2-vaccinated individuals stimulated S+ CD21CD27+ and CD21CD27 Bm cells. Koutsakos, M. et al. Now we can run a single integrated analysis on all cells! Making statements based on opinion; back them up with references or personal experience. select from data frame rows with a condition in r, Split data in R with two specific values of column, Subset a dataframe based on numerical values of a string inside a variable, How to filter based on a specific criteria in R. How to subset data in R: participant only needs to meet one of five criteria? Borcherding, N., Bormann, N. L. & Kraus, G. scRepertoire: an R-based toolkit for single-cell immune receptor analysis. After discussing with colleagues and reading other articles I decided to go for option b). A multiple hypothesis correction procedure was applied to obtain adjusted P values. rowSums () determines how many non-zero counts you have. JCI Insight 2, e92943 (2017). Chang, L. Y., Li, Y. contributed reagents and interpreted data. Gene expression data and TotalSeq surface proteome data were integrated separately. ), A vector of cell names to use as a subset. Nave B cell clusters were identified on the basis of their surface protein expression of CD27, CD21 and IgD and their transcriptional levels of TCLA1, IL4R, BACH2, IGHD and BTG1. 183, 21762182 (2009). 3e and Extended Data Fig. Why typically people don't use biases in attention mechanism? # When adding multimodal data to Seurat, it's okay to have duplicate feature names. ## [7] pbmcsca.SeuratData_3.0.0 pbmcMultiome.SeuratData_0.1.2 Use MathJax to format equations. Prolonged evolution of the human B cell response to SARS-CoV-2 infection. Logical operators ("and", "or") in DOS batch, Difference between Boolean operators && and & and between || and | in R. Why are logical operators in JavaScript left associative? Bm cells can be subdivided into phenotypically and functionally distinct subsets10. I know that I can do subsetting on just one gene in Seurat: However, I want to subset on multiple genes. Short story about swapping bodies as a job; the person who hires the main character misuses his body, Generate points along line, specifying the origin of point generation in QGIS. Preprocessing of raw scRNA-seq data was done as described51. I.E.A. 8d,e). g, Percentages (mean SD) of FcRL4+ Bm cells in paired blood (n=15) and tonsil (n=16) and S+ Bm cells in tonsil samples, separated by SARS-CoV-2-vaccinated (n=8) and recovered patients (n=8). Whereas S+ Bm cells were predominantly resting CD21+ Bm cells at month 6, vaccination strongly induced the appearance of S+ CD21CD27+ and CD21CD27 Bm cells in blood (Fig. No VH or VL chain segments were significantly differentially used between S+ Bm cell subsets. SCT_not_integrated <- FindClusters(SCT_not_integrated) 7d). SCT_integrated <- IntegrateData(anchorset = SCT_Integrated.anchors, normalization.method = "SCT", features.to.integrate = rownames(SCT_Integrated)) ## [15] SeuratObject_4.1.3 Seurat_4.3.0 The interrelatedness between these Bm cell subsets remains unknown. Circulating TFH cells, serological memory, and tissue compartmentalization shape human influenza-specific B cell immunity. Immunity 54, 12901303.e7 (2021). & Kaplan, D. E. Hepatitis C viraemia reversibly maintains subset of antigen-specific T-bet+ tissue-like memory B cells. Science 371, eabf4063 (2021). operators sufficient to make every possible logical expression? The sample code is also provided at the end. Asking for help, clarification, or responding to other answers. filtered_contig_annotations.csv files obtained from the cellranger multipipeline were used as input for the changeo-10x pipeline. By clicking Accept all cookies, you agree Stack Exchange can store cookies on your device and disclose information in accordance with our Cookie Policy. Visualization of the clonal trees was done using dowser66. 8b,c). We used an adaptation of LIBRA-seq68 to identify antigen-specific cells in our sequencing data. Lines connect shared clones. Defining antigen-specific plasmablast and memory B cell subsets in human blood after viral infection or vaccination. We stained S, RBD, nucleocapsid (for tonsil samples), hemagglutinin (for tonsil samples) or a decoy probe using separate fluorochrome-conjugated SAVs. Because we are confident in having identified common cell types across condition, we can ask what genes change in different conditions for cells of the same type. seurat_object <- subset(seurat_object, subset = seurat_object@meta.data[[meta_data]] == 'Singlet'), the name in double brackets should be in quotes [["meta_data"]] and should exist as column-name in the meta.data data.frame (at least as I saw in my own seurat obj). In the SARS-CoV-2 Tonsil Cohort and SARS-CoV-2 Vaccination Cohort, cells with fewer than 200 or more than 4,000 detected genes were excluded from the analysis. 4ac). A.E.M. Dimensionality reduction and clustering analysis of flow cytometry data were performed in R using the CATALYST workflow (CATALYST package, version 1.18.1) (ref. P values are provided if significant (p<0.05) between the S and S+ Bm cell subsets. Cell Rep. 37, 109823 (2021). Rodda, L. B. et al. 5c). I am trying to subset the object based on cells being classified as a 'Singlet' under seurat_object@meta.data[["DF.classifications_0.25_0.03_252"]] and can achieve this by doing the following: I would like to automate this process but the _0.25_0.03_252 of DF.classifications_0.25_0.03_252 is based on values that are calculated and will not be known in advance. | object@dr$pca | object[["pca"]] | All tests were performed two-sided. For scRNA-seq data, distribution was assumed to be normal, but this was not formally tested. ## [79] mathjaxr_1.6-0 ggridges_0.5.4 evaluate_0.20 | NoLegend | Remove all legend elements | SCT_integrated <- FindClusters(SCT_integrated), control_subset <- subset(SCT_integrated, orig.ident = 'Chow') | object@hvg.info | HVFInfo(object = object) | PubMed Central Most functions now take an assay parameter, but you can set a Default Assay to avoid repetitive statements. I have a Seurat object that I have run through doubletFinder. All plotting functions will return a ggplot2 plot by default, allowing easy customization with ggplot2. I was wondering, if it make more sense to find subsetting parameters which will comply with all the samples, or one can do it one sample (or one condition) at a time by itself. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 6 scRNA-seq analysis of B cells in tonsils and blood. 205, 20162025 (2020). Natl Acad. Immunity 51, 398410.e5 (2019). and reading this issue I only got more confused. All samples were analyzed by flow cytometry and paired month 6 and 12 samples from nine patients also by single-cell RNA sequencing (scRNA-seq). 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). 30 most frequently used segments among RBD+ Bm cells are shown. PubMedGoogle Scholar. 22,54). Cell 185, 15881601.e14 (2022). Immunoglobulin signature predicts risk of post-acute COVID-19 syndrome. ), # S3 method for Seurat Commun. Is it safe to publish research papers in cooperation with Russian academics? A longitudinal cohort (Extended Data Fig. Is there a generic term for these trajectories? 7 Phenotypic and functional characterization of circulating S, Extended Data Fig. Peer reviewer reports are available. ## BLAS: /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3 128, 45884603 (2018). Notice that many of the top genes that show up here are the same as the ones we plotted earlier as core interferon response genes. Bioinformatics Stack Exchange is a question and answer site for researchers, developers, students, teachers, and end users interested in bioinformatics. You signed in with another tab or window. First the following steps were performed in the order that they were displayed: SCTransform, SelectIntegrationFeatures, PrepSCTIntegration, FindIntegrationAnchors, IntegrateData, RunPCA and RunUMAP. 16 patients undergoing tonsillectomies for unrelated conditions were included and paired blood and tonsil samples obtained. | RotatedAxis | Rotates x-axis labels |. 35, 255284 (2017). We obtained paired tonsil and peripheral blood mononuclear cell and serum samples. Lines connect paired samples. ## [139] Biobase_2.58.0 numDeriv_2016.8-1.1 shiny_1.7.4. Creates a Seurat object containing only a subset of the cells in the original object. | SetIdent(object = object, ident.use = "new.idents") | Idents(object = object) <- "new.idents" | Immunol. b, Distribution of S+ Bm cell subsets is provided at month 6 preVac, month 12 nonVac and month 12 postVac. Y.Z. Dot plots and medians (right) of frequencies of RBD+ Bm cells at acute infection (n=59) and month 6 (n=61) and 12 post-infection (n=17). ISSN 1529-2908 (print). The correct operator is %in% here. In b, frequencies were compared using a two-tailed Wilcoxon matched-pairs signed rank test. So I have a couple of questions regarding my workflow: For downstream DE analysis, the scale.data slot in the SCT assay has disappeared after integration. c, Dot plot shows expression of selected genes in main B cell populations. Antibody affinity shapes the choice between memory and germinal center B cell fates. ), BRCCH-EDCTP COVID-19 initiative (to A.E.M.) They were also enriched in gene transcripts involved in interferon (IFN)- and BCR signaling and showed high expression of integrins ITGAX, ITGB2 and ITGB7 (Fig. Out of all possible solutions, I feel like performing the analysis as @tilofreiwald's "option b" would be the best. ; and #310030-200669 and #310030-212240 to O.B. VASPKIT and SeeK-path recommend different paths. 4f,g). Hugo. Markers were scaled with arcsinh transformation (cofactor 6,000), samples were subsetted to maximally 25 S+ Bm cells per sample. d, Heatmap displays V light (VL) gene usage in RBD+ and RBD Bm cells from scRNA-seq dataset of SARS-CoV-2-infected patients at month 6 and 12 post-infection. The alternative would be to subset() the population of interest and run the complete preprocessing including integration only on those cells again. As one can see in the pic below, the quality is quite different in each of the duplicated conditions.
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