It works, however, for some types of cells, not very well. https://doi.org/10.1038/s41590-023-01497-y, DOI: https://doi.org/10.1038/s41590-023-01497-y. Hi all, I'm also interested in this issue, and wonder what is the best way to subset and reclustering data starting from an integrating dataset? | WhichCells(object = object, ident.remove = "ident.remove") | WhichCells(object = object, idents = "ident.remove", invert = TRUE) | J. Immunol. 2a) of patient CoV-P1 pre-exposure to SARS-CoV-2, at days 33 and 152 post-symptom onset and at day 12 post-first dose of SARS-CoV-2 mRNA vaccination (that is, day 166 post-symptom onset). 131, e145516 (2021). Poon, M. M. L. et al. a. However, this brings the cost of flexibility. For the same reasons, I felt this was the most intuitive way. Accessing data in Seurat is simple, using clearly defined accessors and setters to quickly find the data needed. Thank you. @timoast , how can we finally tackle this issue? Conversely, the frequency of S+ CD21CD27 Bm cells rose quickly and remained stable over 150days post-vaccination, accounting for about 20% of S+ Bm cells (Fig. e, Heat map shows enrichment scores of selected gene sets that are significantly different between CD27lo/hiCD21+ resting and CD21CD27FcRL5+ S+ Bm cell subsets in a pseudobulk analysis (n=5 individuals). Learn R. Search all packages and functions. | object@dr$pca | object[["pca"]] | 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. Niessl, J. et al. Phenotype, chemokine receptor expression and clonal connections suggested these cells formed from CD21+ resting Bm cells, although we cannot exclude that some might have arisen directly in the tonsils. Seurats centered log ratio transformation was applied across features, followed by a scaling of obtained values, resulting in final LIBRA scores. 67). 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. Choose a subset of cells, and use the integration assay to Run PCA, umap, findneighbors and findclusters to do subclustering. Note, that tested this on one data set only so far. ## [28] ggrepel_0.9.3 rbibutils_2.2.13 textshaping_0.3.6 | FontSize | Set font sizes for various elements of a plot | Article However there are a few times that i found some genes that are primary markers for one certain subtype of the cells i want to sub clustering do not exist in the integration assay, which may lead to some problems. | GetGeneLoadings(object = object, reduction.type = "pca") | Loadings(object = object, reduction = "pca") | 4d). Has the cause of a rocket failure ever been mis-identified, such that another launch failed due to the same problem? Are there any canonical examples of the Prime Directive being broken that aren't shown on screen? B cells that differentiate in the GC undergo affinity maturation through somatic hypermutation (SHM) of the B cell receptor (BCR) following which B cells can become long-lived plasma cells or Bm cells4,5,6. (palm-face-impact)@MariaKwhere were you 3 months ago?! seurat_subset <- SubsetData (seurat_object, subset.name = neuron_ids [1], accept.low = 0.1) However, I want to subset on multiple genes. ## [7] LC_PAPER=en_US.UTF-8 LC_NAME=C 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: | [email protected] | GetAssayData(object = object, slot = "counts") | The beginning of pseudotime was manually set inside the partition with mostly unswitched B cells. The heterogeneity of Bm cells could be explained by several models38,39. a, Dot plots and medians of frequencies of S+ Bm cells are provided at baseline (n=10), week 2 post-second dose (n=10) and month 6 post-second dose (n=11). b, Representative flow cytometry plots show gating strategy for RBD+ Bm cells in patient CoV-P1, as in Fig. As suggested by #2042, you can change the set of features to be integrated by using the features.to.integrate argument in IntegrateData. Use of this site constitutes acceptance of our User Agreement and Privacy ; #323530-177975 to S.A.; #323530-191220 to C.C. control_subset <- FindClusters(control_subset). To subscribe to this RSS feed, copy and paste this URL into your RSS reader. The point is that you need a series of single comparisons, not a comparison of a series of options. Science 371, eabf4063 (2021). Seurat v4 includes a set of methods to match (or align) shared cell populations across datasets. Takes either a list of cells to use as a subset, or a Sci. d, Violin plots comparing frequencies of CD21CD27+, CD21CD27, CD21+CD27+ and CD21+CD27 S+ Bm cell subsets are separated by timepoints post-infection and mild (acute infection, n=15; month 6, n=33; month 12, n=10) and severe COVID-19 (acute infection, n=8; month 6, n=19; month 12, n=6). Hopp, C. S. et al. Sign up for the Nature Briefing newsletter what matters in science, free to your inbox daily. Multifactorial seroprofiling dissects the contribution of pre-existing human coronaviruses responses to SARS-CoV-2 immunity. c, Frequency (median interquartile range) of S+ (left) and N+ (right) GC B cells within total B cells are given in tonsils of SARS-CoV-2-vaccinated and in recovered individuals. 7ac). Cell 183, 12981311.e11 (2020). PhenoGraph clustering identified an IgG+CD21CD27 cluster (cluster 2), which was TbethiCD11c+FcRL5+, and CD21CD27+ clusters characterized by high expression of CD71, Blimp-1 and Ki-67 (clusters 1, 7 and 8) (Extended Data Fig. IFN induces epigenetic programming of human T-bethi B cells and promotes TLR7/8 and IL-21 induced differentiation. ## [19] ROCR_1.0-11 limma_3.54.1 globals_0.16.2 Ogega, C. O. et al. If NULL In c and g, all P values are shown, in the other graphs adjusted P values are shown if significant (p<0.05). 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. Hi All, We would all appreciate it if @timoast or others from the @satijalab can chime in. 6g and Extended Data Fig. d, Shown are representative histograms of Ki-67 in patient CoV-P2 (left) and violin plots of percentages of Ki-67+ S+ Bm cells compared with S Bm cells (right) at indicated timepoints. Thank you @satijalab for this amazing tool and the amazing tutorials !!!! 1a and Supplementary Table 1). Seurat is great for scRNAseq analysis and it provides many easy-to-use ggplot2 wrappers for visualization. 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. Multi-Assay Features 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). ## [7] pbmcsca.SeuratData_3.0.0 pbmcMultiome.SeuratData_0.1.2 SARS-CoV-2-specific Bm cells were identified using probes of biotinylated SARS-CoV-2 spike (S) and receptor-binding domain (RBD) protein multimerized with fluorophore-labeled streptavidin (SAV) and characterized using a 28-color spectral flow cytometry panel (Fig. Which of course included re-calculating the variable genes (on the "RNA" Slot) and re-integration. Another useful way to visualize these changes in gene expression is with the split.by option to the FeaturePlot() or VlnPlot() function. 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. Immunoglobulin signature predicts risk of post-acute COVID-19 syndrome. PubMed Victora, G. D. & Nussenzweig, M. C. Germinal centers. Each set of modal data (eg. Use the Previous and Next buttons to navigate the slides or the slide controller buttons at the end to navigate through each slide. These authors contributed equally: Yves Zurbuchen, Jan Michler. 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. dg, Stacked bar graphs display tissue (d) and isotype distribution (e) in Bm cell clusters, and isotype (f) and cluster distribution (g) in SWT+ Bm cells in tonsils and blood. Comparison of V heavy and light chain usage within S+ Bm cell subsets in the scRNA-seq data from SARS-CoV-2-recovered individuals (months 6 and 12 post-infection) revealed very similar chain usage in S+ CD21+ resting (CD21+CD27+ and CD21+CD27 combined), CD21CD27+CD71+ activated and CD21CD27FcRL5+ Bm cells (Extended Data Fig. control_subset <- RunPCA(control_subset, npcs = 30, verbose = FALSE, features = Variable Features(control_subset)), AverageExpression: Averaged feature expression by identity class Nat. They donated blood before vaccination, at days 813 (week 2) post-second dose, 6months after the second dose and days 1114 post-third dose. Already on GitHub? Sci. Human T-bet governs the generation of a distinct subset of CD11chighCD21low B cells. 6, eabk0894 (2021). Rev. # 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. # split the dataset into a list of two seurat objects (stim and CTRL), # normalize and identify variable features for each dataset independently, # select features that are repeatedly variable across datasets for integration, # this command creates an 'integrated' data assay, # specify that we will perform downstream analysis on the corrected data note that the, # original unmodified data still resides in the 'RNA' assay, # Run the standard workflow for visualization and clustering, # For performing differential expression after integration, we switch back to the original, ## CTRL_p_val CTRL_avg_log2FC CTRL_pct.1 CTRL_pct.2 CTRL_p_val_adj, ## GNLY 0 6.006173 0.944 0.045 0, ## FGFBP2 0 3.243588 0.505 0.020 0, ## CLIC3 0 3.461957 0.597 0.024 0, ## PRF1 0 2.650548 0.422 0.017 0, ## CTSW 0 2.987507 0.531 0.029 0, ## KLRD1 0 2.777231 0.495 0.019 0, ## STIM_p_val STIM_avg_log2FC STIM_pct.1 STIM_pct.2 STIM_p_val_adj, ## GNLY 0.000000e+00 5.858634 0.954 0.059 0.000000e+00, ## FGFBP2 3.408448e-165 2.191113 0.261 0.015 4.789892e-161, ## CLIC3 0.000000e+00 3.536367 0.623 0.030 0.000000e+00, ## PRF1 0.000000e+00 4.094579 0.862 0.057 0.000000e+00, ## CTSW 0.000000e+00 3.128054 0.592 0.035 0.000000e+00, ## KLRD1 0.000000e+00 2.863797 0.552 0.027 0.000000e+00, ## p_val avg_log2FC pct.1 pct.2 p_val_adj, ## ISG15 1.212995e-155 4.5997247 0.998 0.239 1.704622e-151, ## IFIT3 4.743486e-151 4.5017769 0.964 0.052 6.666020e-147, ## IFI6 1.680324e-150 4.2361116 0.969 0.080 2.361359e-146, ## ISG20 1.595574e-146 2.9452675 1.000 0.671 2.242260e-142, ## IFIT1 3.499460e-137 4.1278656 0.910 0.032 4.917791e-133, ## MX1 8.571983e-121 3.2876616 0.904 0.115 1.204621e-116, ## LY6E 1.359842e-117 3.1251242 0.895 0.152 1.910986e-113, ## TNFSF10 4.454596e-110 3.7816677 0.790 0.025 6.260044e-106, ## IFIT2 1.290640e-106 3.6584511 0.787 0.035 1.813736e-102, ## B2M 2.019314e-95 0.6073495 1.000 1.000 2.837741e-91, ## PLSCR1 1.464429e-93 2.8195675 0.794 0.117 2.057961e-89, ## IRF7 3.893097e-92 2.5867694 0.837 0.190 5.470969e-88, ## CXCL10 1.624151e-82 5.2608266 0.640 0.010 2.282419e-78, ## UBE2L6 2.482113e-81 2.1450306 0.852 0.299 3.488114e-77, ## PSMB9 5.977328e-77 1.6457686 0.940 0.571 8.399938e-73, ## Platform: x86_64-pc-linux-gnu (64-bit), ## BLAS: /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3, ## LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/liblapack.so.3, ## [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C, ## [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8, ## [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8, ## [7] LC_PAPER=en_US.UTF-8 LC_NAME=C, ## [9] LC_ADDRESS=C LC_TELEPHONE=C, ## [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C, ## [1] stats graphics grDevices utils datasets methods base, ## [1] cowplot_1.1.1 ggplot2_3.4.1, ## [3] patchwork_1.1.2 thp1.eccite.SeuratData_3.1.5, ## [5] stxBrain.SeuratData_0.1.1 ssHippo.SeuratData_3.1.4, ## [7] pbmcsca.SeuratData_3.0.0 pbmcMultiome.SeuratData_0.1.2, ## [9] pbmc3k.SeuratData_3.1.4 panc8.SeuratData_3.0.2, ## [11] ifnb.SeuratData_3.1.0 hcabm40k.SeuratData_3.0.0, ## [13] bmcite.SeuratData_0.3.0 SeuratData_0.2.2, ## [15] SeuratObject_4.1.3 Seurat_4.3.0. IgG1 represented the most common subtype (around 65% of S+ Bm cells at months 6 and 12 post-infection), and between 5% and 10% of S+ Bm cells were IgA+ (Fig. Google Scholar. Dominguez, C. X. et al. Hoehn, K. B., Pybus, O. G. & Kleinstein, S. H. Phylogenetic analysis of migration, differentiation, and class switching in B cells. it makes no sense to me the not to use the integrated assay on every downstream analysis. ident.remove = NULL, But I'm also curious how others approach this! Lines connect samples of same individual. Graphical representations were generated with BioRender.com. By clicking Accept all cookies, you agree Stack Exchange can store cookies on your device and disclose information in accordance with our Cookie Policy. Andrews, S. F. et al. ## [136] rmarkdown_2.20 Rtsne_0.16 spatstat.explore_3.0-6 Hi all, 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? This revealed a potent induction of S+ IgG+ Bm cells at week 2 post-second dose, which stably persisted to month 6 post-second dose, and the frequency further increased early post-third dose compared with month 6 post-second dose (Extended Data Fig. Immunol. Freudenhammer, M., Voll, R. E., Binder, S. C., Keller, B. The cohort size was based on sample availability. Whereas subdivision of labor in terms of tissue homing and effector functions has been well characterized for memory T cells, functionally different subsets also exist for memory B (Bm) cells. Density plots indicate count distributions across binding score ranges are shown on top and on the side. Nat. 1b. CD21+ resting Bm cells became prevalent at 612months post-infection. While functions exist within Seurat to perform DE analysis, the p-values from these analyses are often inflated as each cell is treated as an independent . Koutsakos, M. et al. Provided by the Springer Nature SharedIt content-sharing initiative, Nature Immunology (Nat Immunol) Anti-SARS-CoV-2 antibodies were measured by a commercially available enzyme-linked immunosorbent assay specific for S1 of SARS-CoV-2 (Euroimmun SARS-CoV-2 IgG and IgA)57 or by a bead-based multiplexed immunoassay58. In b, significant differences between groups were determined by constructing a bootstrap delta distribution for each pair of unique values between groups. VASPKIT and SeeK-path recommend different paths. As cell identity is only available after intergration and clustering? Browse other questions tagged, Where developers & technologists share private knowledge with coworkers, Reach developers & technologists worldwide. contributed to patient recruitment and data collection. 269, 118129 (2016). 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, Manually define clusters in Seurat and determine marker genes, Trim Seurat object to contain expression info only for selected genes, Seurat VlnPlot presenting expression of multiple genes in a single cluster. after integration I subsetted my cells of interest and did SCTransform on the RNA assay for clustering, but for DE I used the RNA assay, as it is officially recommended (from what I understand, the batch effects are still there). 1 Answer Sorted by: 1 There are a few ways to address this. Y.Z. # 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. Transl. 124, 10171030 (1966). 3d). ## [64] pkgconfig_2.0.3 sass_0.4.5 uwot_0.1.14 I'm writing here to be sure to receive an email when somebody will post an explanation here :-). Cyster, J. G. & Allen, C. D. C. B cell responses: cell interaction dynamics and decisions. a, Scatter plot comparing binding scores (LIBRA-Score) was determined from scRNA-seq for SWT and RBD binding, with every dot representing a cell. ## locale: English version of Russian proverb "The hedgehogs got pricked, cried, but continued to eat the cactus", Effect of a "bad grade" in grad school applications. The B cell response to different pathogens uses tailored effector mechanisms and results in functionally specialized memory B (Bm) cell subsets, including CD21+ resting, CD21CD27+ activated and CD21CD27 Bm cells. Cell 177, 524540 (2019). filtration). Here we showed that single severe acute respiratory syndrome coronavirus 2-specific Bm cell clones showed plasticity upon antigen rechallenge in previously exposed individuals. Antibody affinity shapes the choice between memory and germinal center B cell fates. Andreas E. Moor or Onur Boyman. 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. b, Cohort overview of SARS-CoV-2 Tonsil Cohort. Academic theme for After subsetting clusters of interest (subsetting by ident) I have a Seurat object with RNA, SCT and integrated assay, and dimensional reduction (pca, tsne, umap) coming from the original Seurat object. designed and performed scRNA-seq experiments, and analyzed and interpreted data. Cutting edge: B cellintrinsic T-bet expression is required to control chronic viral infection. As a result, the subset() call would only return rows where bf11 was TRUE (or something that evaluated to TRUE). USA 104, 97709775 (2007). 4f,g). Nat. ## other attached packages: We found that S+ CD21CD27 Bm cells showed signs of increased antigen processing and presentation; how much this might translate into truly increased capacity of antigen presentation is unclear43. Is it possible and valid instead to use values from the "data" slot of the SCT assay (log-normalized corrected values) for the MAST test? However I did the following: Next I perform FindConservedMarkers on each of the cell clusters to identify conserved gene markers for each cell cluster. In this article, we studied the kinetics, distribution and interrelatedness of antigen-specific Bm cell subsets during acute infection and months 6 and 12 post-infection with SARS-CoV-2 in individuals with mild and severe coronavirus disease 2019 (COVID-19) that have also received SARS-CoV-2 messenger RNA vaccination post-infection, and healthy volunteers before and after SARS-CoV-2-specific vaccination. I have similar questions as @attal-kush with regards to reclustering of a subset of an integrated object. Below, we demonstrate how to modify the Seurat integration workflow for datasets that have been normalized with the sctransform workflow. ## But I am not sure which assay should be used for FindVariableFeatures of the subset cells, RNA, SCT, or Integrated? Statistical significance was established at P<0.05. Collectively, these data identify a durable, IgG1-dominated S+ Bm cell response forming upon SARS-CoV-2 infection. Immunity 52, 842855.e6 (2020). The method is named sctransform, and avoids some of the pitfalls of standard normalization workflows, including the addition of a pseudocount, and log-transformation. If split.by is not NULL, the ncol is ignored so you can not arrange the grid. Samples were acquired on a Cytek Aurora cytometer using the SpectroFlo software. Antigen-specific CD21CD27+ and CD21CD27 Bm cells have been transiently detected after vaccines12,19,20,21,22 and during infection with certain pathogens21,23,24, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (refs. designed experiments and interpreted data. 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. Cells are colored by timepoint (left) and by clusters identified by PhenoGraph algorithm (right). The code generated during the current study is available at https://github.com/Moors-Code/MBC_Plasticity_Moor_Boyman_Collaboration. 65). Durable SARS-CoV-2 B cell immunity after mild or severe disease. Mean diversity index (line) and confidence intervals (transparent shadings) are shown. ## [11] ifnb.SeuratData_3.1.0 hcabm40k.SeuratData_3.0.0 7, eabq3277 (2022). 6h). Then we use FindMarkers() to find the genes that are different between stimulated and control B cells. These dynamics were comparable in patients with mild and severe COVID-19 (Extended Data Fig. & Cancro, M. P. Age-associated B cells: key mediators of both protective and autoreactive humoral responses. To subscribe to this RSS feed, copy and paste this URL into your RSS reader. 59). Sci. 4h). f, Violin plots show percentages of IgG1+ (left) and IgG3+ (right) S+ Bm cells at indicated timepoints (acute, n=23; month 6, n=52; month 12, n=16). Convergent antibody responses to SARS-CoV-2 in convalescent individuals. To subscribe to this RSS feed, copy and paste this URL into your RSS reader. P values in e and g are shown if significant. ## [124] gridExtra_2.3 parallelly_1.34.0 codetools_0.2-18 Genewise statistics were conducted using empirical Bayes quasi-likelihood F-tests. original object. Knox, J. J. et al. Takes either a list of cells to use as a subset, or a parameter (for example, a gene), to subset on. Peer reviewer reports are available. Note that @timoast from the Seurat team recommended otherwise, although I never seen an explanation why would this not best way to go. Primary Handling Editor: Ioana Visan in collaboration with the Nature Immunology team. and O.B. Adjusted P values are shown if significant (p<0.05). JCI Insight 2, e92943 (2017). Efficient recall of Omicron-reactive B cell memory after a third dose of SARS-CoV-2 mRNA vaccine. To visualize the two conditions side-by-side, we can use the split.by argument to show each condition colored by cluster. i, SHM counts are provided for nave B cells (n=1,607), blood (n=170) and tonsillar SWT+ Bm cells (n=1,128). Dan, J. M. et al. Generate points along line, specifying the origin of point generation in QGIS. ## loaded via a namespace (and not attached): Samples were compared using paired t-test (c) or two-sided Wilcoxon test (f). I can figure out what it is by doing the following: Where meta_data = 'DF.classifications_0.25_0.03_252' and is a character class.
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