## [31] xfun_0.37 dplyr_1.1.0 crayon_1.5.2 Sample assignment of cells was done using TotalSeq-based cell hashing and Seurats HTODemux() function. "~/Downloads/pbmc3k/filtered_gene_bc_matrices/hg19/", # Get cell and feature names, and total numbers, # Set identity classes to an existing column in meta data, # Subset Seurat object based on identity class, also see ?SubsetData, # Subset on the expression level of a gene/feature, # Subset on a value in the object meta data, # Downsample the number of cells per identity class, # View metadata data frame, stored in object@meta.data, # Retrieve specific values from the metadata, # Retrieve or set data in an expression matrix ('counts', 'data', and 'scale.data'), # Get cell embeddings and feature loadings, # FetchData can pull anything from expression matrices, cell embeddings, or metadata, # Dimensional reduction plot for PCA or tSNE, # Dimensional reduction plot, with cells colored by a quantitative feature, # Scatter plot across single cells, replaces GenePlot, # Scatter plot across individual features, repleaces CellPlot, # New things to try! # HoverLocator replaces the former `do.hover` argument It can also show extra data throught the `information` argument, # designed to work smoothly with FetchData, # FeatureLocator replaces the former `do.identify`, # Run analyses by specifying the assay to use, # Pull feature expression from both assays by using keys, # Plot data from multiple assays using keys, Fast integration using reciprocal PCA (RPCA), Integrating scRNA-seq and scATAC-seq data, Demultiplexing with hashtag oligos (HTOs), Interoperability between single-cell object formats, Set font sizes for various elements of a plot. In d, frequencies were compared using a two-tailed, two-proportions z-test with a Bonferroni-based multiple testing correction. Generic Doubly-Linked-Lists C implementation. Making statements based on opinion; back them up with references or personal experience. a, Heatmap compares V heavy (VH; left) and VL (right) gene usage in indicated S+ Bm cell subsets and S Bm cells (non-binders) from scRNA-seq data of SARS-CoV-2-infected patients at months 6 and 12 post-infection. I am worried that the top variable features of the original Seurat Object are not the same variable features of the new subset. a, Donut plots of BCR sequences of S+ Bm cells in three representative patients preVac and postVac. 4e). Thanks for contributing an answer to Stack Overflow! As you can see, many of the same genes are upregulated in both of these cell types and likely represent a conserved interferon response pathway. a, Scatter plot comparing binding scores (LIBRA-Score) was determined from scRNA-seq for SWT and RBD binding, with every dot representing a cell. 3d). 1a). 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. ## Matrix products: default 2a and 3c). Making statements based on opinion; back them up with references or personal experience. What are the advantages of running a power tool on 240 V vs 120 V? 1b and Supplementary Table 3) comprised subjects seen at University Hospital Zurich between November 2021 and April 2022 that underwent tonsillectomy for recurrent and chronic tonsillitis or obstructive sleep apnea and were exposed to SARS-CoV-2 by infection and/or vaccination. The following tutorial is designed to give you an overview of the kinds of comparative analyses on complex cell types that are possible using the Seurat integration procedure. Naradikian, M. S., Hao, Y. For example, we can calculated the genes that are conserved markers irrespective of stimulation condition in cluster 6 (NK cells). Freudenhammer, M., Voll, R. E., Binder, S. C., Keller, B. ## [46] scales_1.2.1 mvtnorm_1.1-3 spatstat.random_3.1-3 operators sufficient to make every possible logical expression? I am also stuck on this issue too. 9e). Hugo. By clicking Post Your Answer, you agree to our terms of service, privacy policy and cookie policy. 1a and Supplementary Table 1). Everyone: I strongly suggest using the RNA assay for all DE. Pseudotime-based trajectory analysis using Monocle 3 in our scRNA-seq dataset (Extended Data Fig. ## [3] patchwork_1.1.2 thp1.eccite.SeuratData_3.1.5 Several of these differences, such as T-bet, and CD11c, were confirmed at the protein level (Fig. BCR diversity was slightly reduced in S+ CD21CD27FcRL5+ compared with S+ CD21+ resting Bm cells (Extended Data Fig. Downstream analysis was conducted in R version 4.1.0 mainly with the package Seurat (v4.1.1) (ref. CD21+ resting Bm cells became prevalent at 612months post-infection. PubMed I did see batch effects here (cells from different batches did not share clusters). The sequencing data have been deposited at Zenodo at https://doi.org/10.5281/zenodo.7064118. The code could only make sense if the data is a square, equal number of rows and columns. f, Violin plots of IgG1+ (left) and IgG3+ percentages (right) are shown in each S+ Bm cell subset from the same samples as in e. g, Pie charts represent percentages of S+ Bm cells among all cells in scRNA-seq dataset, separated by Bm cell subsets. Haghverdi, L., Lun, A. T. L., Morgan, M. D. & Marioni, J. C. Batch effects in single-cell RNA-sequencing data are corrected by matching mutual nearest neighbors. Transl. 12, 6703 (2021). To learn more, see our tips on writing great answers. I wonder if anyone has found a definitive answer for this? SHM counts were low in unswitched S+ CD21+ Bm cells, slightly higher in CD21+CD27 resting Bm cells, and high by comparison in CD21+CD27+ resting, CD21CD27+CD71+ activated and CD21CD27 Bm cells (Fig. UMAP and clustering grouped Bm cells by IgG (clusters 15), IgM (clusters 6 and 7) and IgA (clusters 8 and 9) expression and revealed a phenotypical shift from acute infection to months 6 and 12 post-infection characterized by increased expression of CD21 on S+ Bm cells, whereas expression of Blimp-1, Ki-67, CD11c, CD71 and FcRL5 diminished (Extended Data Fig. 5f,g). Look at what 1||2||3 evaluates to: and you'd get the same using | instead. ## [133] parallel_4.2.0 grid_4.2.0 tidyr_1.3.0 Front Immunol. Med. The various Bm cell subsets could comprise entirely separate lineages, with distinct BCR repertoires. Analysis of SARS-CoV-2-specific GC Bcl-6+Ki-67+ B cells detected a trend towards elevated frequencies of S+ and N+ GC cells in recovered compared with vaccinated subjects (Extended Data Fig. We found that SARS-CoV-2 infection and vaccination induced long-lived and stable antigen-specific Bm cells in the circulation that continued to mature up to 1year post-infection, as evidenced by their elevated proliferation rate at month 6, high SHM counts and improved breadth of SARS-CoV-2 antigen recognition. Blood 99, 15441551 (2002). 6dg). Lines connect samples of same individual. ## LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/liblapack.so.3 By clicking Accept all cookies, you agree Stack Exchange can store cookies on your device and disclose information in accordance with our Cookie Policy. Bm cells are colored by cluster (f, left), tissue origin (f, right) or SWT binding (g). e and f, UMAP represents Monocle 3 analysis on all Bm cells in scRNA-seq dataset, colored by clusters identified (e) or pseudotime annotation (f). 4ac). I would also like to know the recommended way of doing this. subsetting seurat object with multiple samples. Is it necessary to run FindVariableFeatures on the RNA assay of the subset and get new variables to use in PCA in order to properly cluster the subset? This is because the RNA slot is a true representative of biological variation, when someone tries to reproduce your findings they won't perform a negative binomial regression on their PCR. Andrews, S. F. et al. Is there a way to do that? Generally, you'll want use different parameters for each sample. & Shlomchik, M. J. Germinal center and extrafollicular B cell responses in vaccination, immunity, and autoimmunity. | StashIdent(object = object, save.name = "saved.idents") | object$saved.idents <- Idents(object = object) | I have a Seurat object that I have run through doubletFinder. Immunoglobulin signature predicts risk of post-acute COVID-19 syndrome. Nature 604, 141145 (2022). Antigen-stimulated B cells receiving instructive signals from their interaction with helper CD4+ T cells can further differentiate in the germinal centers (GCs) of secondary lymphoid organs or using an extrafollicular pathway. Monty Hall problem- a peek through simulation, Modeling single cell RNAseq data with multinomial distribution, negative bionomial distribution in (single-cell) RNAseq, clustering scATACseq data: the TF-IDF way, plot 10x scATAC coverage by cluster/group, stacked violin plot for visualizing single-cell data in Seurat. Find corresponding symbol for gene used in Seurat, Subsetting a Seurat object based on colnames. | NoLegend | Remove all legend elements | 6g and Extended Data Fig. and O.B. | Seurat v2.X | Seurat v3.X | How about saving the world? Nat Immunol (2023). Cell 185, 18751887.e8 (2022). Human T-bet governs the generation of a distinct subset of CD11chighCD21low B cells. Bioinformatics 32, 28472849 (2016). JCI Insight 2, e92943 (2017). Nowicka, M. et al. Barnett, B. E. et al. 9b). | WhichCells(object = object, max.cells.per.ident = 500) | WhichCells(object = object, downsample = 500) | rowSums () determines how many non-zero counts you have. 1c and Supplementary Table 4) with no history of SARS-CoV-2 infection and seronegative for SARS-CoV-2 S S1-specific antibodies. F1000Res. Bm cells specific for RBD, wild-type spike (SWT) or spike variants B.1.351 (Sbeta) and B.1.617.2 (Sdelta) were identified by SAV multimers carrying specific oligonucleotide barcodes. # To pull data from an assay that isn't the default, you can specify a key that's linked to an assay for feature pulling. ), Innovation grant of University Hospital Zurich (to O.B. Rev. The standard Seurat workflow takes raw single-cell expression data and aims to find clusters within the data. Site design / logo 2023 Stack Exchange Inc; user contributions licensed under CC BY-SA. | object@var.genes | VariableFeatures(object = object) | The cohort size was based on sample availability. Transl. 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). Differential gene expression identified higher expression of CR2, CD44, CCR6 and CD69 in tonsillar SWT+ Bm cells compared with blood SWT+ Bm cells, whereas the activation-related genes FGR and CD52 were higher in blood SWT+ Bm cells compared with their tonsillar counterparts (Extended Data Fig. a) My approach would be to just run FindClusters() with a higher resolution on the whole dataset until the desired subclustering is reached. Koutsakos, M. et al. J.M. c, Pie chart show the percentage of SWT binders that also bind RBD in scRNA-seq dataset. The transcription factor T-bet resolves memory B cell subsets with distinct tissue distributions and antibody specificities in mice and humans. We included a total of 65 patients of the full cohort51,52 on the basis of a power calculation from pre-experiments and according to sample availability of at least paired samples from two timepoints. 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. During acute infection S+ Bm cells were mainly immunoglobulin (Ig)M+ and IgG+, whereas IgG+ Bm cells predominated (8590%) at months 6 and 12 post-infection (Fig. But I especially don't get why this one did not work: PLoS Comput. IFN induces epigenetic programming of human T-bethi B cells and promotes TLR7/8 and IL-21 induced differentiation. As the proof is in the pudding, I decided to try different approaches on my own data and share my findings here. Density plots indicate count distributions across binding score ranges are shown on top and on the side. Atypical B cells up-regulate costimulatory molecules during malaria and secrete antibodies with T follicular helper cell support. To subset the Seurat object, the SubsetData() function can be easily used. Extended Data Fig. I tried. Hi Seurat team, Thank you for developing Seurat. I have a seurat object with 10 samples (5 in duplicates). Mean diversity index (line) and confidence intervals (transparent shadings) are shown. At month 6 post-infection (pre-vaccination), 80% of those 30 clones had a CD21+ resting Bm cell phenotype (Fig. then the answer is to run it on the integrated assay). For this, a count matrix was created with HC/LC segments as rows and samples as columns. Ritchie, M. E. et al. to your account. CD21 Bm cells were the predominant subsets during acute infection and early after severe acute respiratory syndrome coronavirus 2-specific immunization. Of these individuals, 35 received one or two doses of SARS-CoV-2 mRNA vaccination between month 6 and month 12, and three subjects were vaccinated between acute infection and month 6 (Supplementary Table 1 and Extended Data Fig. Updated triggering record with value from related record. Commun. Resulting scores were used to compute fold changes and significance levels for enrichment score comparisons between cell subsets in limma (v3.50.3) (ref. 3 Identification of SARS-CoV-2 S, Extended Data Fig. g, Comparison of somatic hypermutation (SHM) counts are provided in SWT+ Bm cells at indicated timepoints (week 2 post-second dose, n=174 cells; month 6 post-second dose, n=271 cells; week 2 post-third dose, n=698 cells). By clicking Accept all cookies, you agree Stack Exchange can store cookies on your device and disclose information in accordance with our Cookie Policy. 1b. Samples in cf were compared using KruskalWallis test with Dunns multiple comparison, showing adjusted P values. Gene expression data and TotalSeq surface proteome data were integrated separately. Imprinted SARS-CoV-2-specific memory lymphocytes define hybrid immunity. The scRNA-seq dataset identified a significantly increased SHM count in S+ Bm cells at month 12 compared with month 6 post-infection (Fig. ## locale: ## [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8 Frequencies of S+ Bm cells were comparable in patients with mild and severe COVID-19 (Fig. K.W. All plotting functions will return a ggplot2 plot by default, allowing easy customization with ggplot2. *P<0.05, **P<0.01, ***P<0.001, ****P<0.0001. Seurat v4 includes a set of methods to match (or align) shared cell populations across datasets. The beginning of pseudotime was manually set inside the partition with mostly unswitched B cells. CD21CD27 Bm cells were reported to be able to secrete antibodies when receiving T cell help and to act as antigen-presenting cells24. Did the Golden Gate Bridge 'flatten' under the weight of 300,000 people in 1987? sessionInfo()## R version 4.2.0 (2022-04-22) Single-cell trajectories were created with Monocle3 (version 1.2.9) (ref. b, N+ (left) and S+ (right) Bm cell frequencies were determined in paired blood and tonsils of SARS-CoV-2-vaccinated (n=8) and SARS-CoV-2-recovered individuals (n=8). In the SARS-CoV-2 Infection Cohort, cells with fewer than 200 or more than 2,500 detected genes and cells with more than 10% detected mitochondrial genes were excluded from the analysis. h, Volcano plot shows transcript levels in SWT+ Bm cell in tonsils and blood. During acute infection S+ CD21CD27+ Bm cells and CD21CD27 Bm cells represented on average 48.1% and 16.4% of total S+ Bm cells, respectively, and they strongly declined at month 6 (6.3% and 5.3%) and month 12 (3.7% and 6.6%) post-infection (Fig. If split.by is not NULL, the ncol is ignored so you can not arrange the grid. ## [34] jsonlite_1.8.4 progressr_0.13.0 spatstat.data_3.0-0 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. Developed by Paul Hoffman, Satija Lab and Collaborators. 351 2 15. 6, eabh0891 (2021). For scRNA-seq data, distribution was assumed to be normal, but this was not formally tested. Are || and ! Learn more about Stack Overflow the company, and our products. The num_dim parameter of Monocles preprocess_cds() function was set to 20. Frozen mononuclear cells were stained in 96-well U-bottom plates using ZombieUV Live-Dead staining (BioLegend) and TruStain FcX (1:200, BioLegend) in PBS for 30min, followed by staining with the above-mentioned antigen-specific staining mix (200ng S, 50ng RBD, 100ng nucleocapsid, 100ng hemagglutinin and 20ng SAV-decoy per color per 50l) at 4C for 1h. Subsequently, cells were stained for 30min with surface markers, followed by fixation and permeabilization with transcription factor staining buffer (eBioscience) at room temperature for 1h and intracellular staining at room temperature for 30min, before washing and acquisition.
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