Many, many thanks for the great package and continued support! Single-cell RNA-seq: Pseudobulk differential expression analysis On the basis of our data, we suggest a linearplastic model where the antigen stimulation and GC maturation of SARS-CoV-2-specific B cells resulted in the gradual adoption of a CD21+Ki-67lo resting Bm cell state at months 612 post-infection. rev2023.4.21.43403. ## [1] systemfonts_1.0.4 sn_2.1.0 plyr_1.8.8 Our work also provides insight into the CD21CD27 Bm cells, which made up a sizeable portion of Bm cells following acute viral infection and vaccination in humans. ## Article 7e,f). cells = NULL, 6h). 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. While I did not test the above, I tested running FindVariableFeatures() (or not), and I recommend re-running FindVariableFeatures(). 4h). 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). Replies here and in some other GitHub issues have slightly different approaches but they all make general sense. ## [55] reticulate_1.28 stats4_4.2.0 htmlwidgets_1.6.1 Thanks for contributing an answer to Stack Overflow! Numbers indicate percentages of parent population. So I guess FindVariableFeatures of the subset cells should be tried. PubMed Central Why are these constructs using pre and post-increment undefined behavior? To identify canonical cell type marker genes that are conserved across conditions, we provide the FindConservedMarkers() function. Upon encounter with cognate antigens, lymphocytes are endowed with the capacity to form memory cells1,2. WNN clustering of all sequenced Bm cells identified ten clusters that, on the basis of the expression of cell surface markers and Ig isotype, were merged into five subsets annotated as CD21CD27+CD71+ activated Bm cells, CD21CD27FcRL5+ Bm cells, CD21+CD27 resting Bm cells, CD21+CD27+ resting Bm cells and unswitched CD21+ Bm cells (Fig. scRNA-seq was performed on samples from nine patients of the SARS-CoV-2 Infection Cohort (Supplementary Table 2), three of the SARS-CoV-2 Vaccination Cohort, and paired blood and tonsil samples of four patients of the SARS-CoV-2 Tonsil Cohort (two recovered and two only vaccinated). Pseudotime-based trajectory analysis using Monocle 3 in our scRNA-seq dataset (Extended Data Fig. 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. Hi All, 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). c, Stacked bar plots (mean+standard deviation) represent isotypes in blood and tonsillar S+ Bm cells from both SARS-CoV-2-vaccinated and SARS-CoV-2-recovered individuals (n=16; also applies to d and e). high.threshold = Inf, It only takes a minute to sign up. I used ?%in% but it didn't work. Note that @timoast from the Seurat team recommended otherwise, although I never seen an explanation why would this not best way to go. 9e). Subsets and markers of antigen-specific B cells and antigen-specific B cell subsets were evaluated only if more than nine or three specific cells per sample were detected, respectively. Nature 602, 148155 (2021). The inclusion of patients with severe COVID-19 will have increased the average age of our cohort, whereas the individuals from which the tonsil samples were obtained were younger on average. Clonal diversity between Bm cell subsets was investigated using the alphaDiversity function of Immcantations package Alakazam (v1.2.0) (ref. SARS-CoV-2 infection generates tissue-localized immunological memory in humans. Sci. 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. T-bet+ B cells have a protective role in mouse models of acute and chronic viral infections38,42. From my understanding, including all genes into the "Feature.to.integrate" functions will give you a gene matrix of all genes altered based on the integration, but the PCA analysis and subsequent non-linear dimensionality reduction and clustering will still be calculated based on the 2000 features found in the "Find.Integration.anchors" functions (unless otherwise stated), which change depending on the original data used, ie subsetted or whole. Unexpected uint64 behaviour 0xFFFF'FFFF'FFFF'FFFF - 1 = 0? The code could only make sense if the data is a square, equal number of rows and columns. Differential gene expression analyses were done using assay RNA of the integrated datasets. I think the proper way is to subset before integration as in Smillie et al. 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 Seurat team, Thank you for developing Seurat. The pro of this approach is that I use this method to solve the problem in the previous approach and now i have the genes that are primary markers for the cell sub types. The pro of this approach is that I use this method to solve the problem in the previous approach and now i have the genes that are primary markers for the cell sub types. 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). Hi Team Seurat, c, Cohort overview of SARS-CoV-2 Vaccination Cohort. e, Violin plots of geometric mean fluorescence intensities (gMFI) or percentages of indicated markers in S+ Bm cells at indicated time points. Signature of long-lived memory CD8+ T cells in acute SARS-CoV-2 infection. a, Flow cytometry plots show decoy S+ (top) and nucleocapsid (N)+ Bm cells (bottom) in paired tonsil and blood samples of a SARS-CoV-2-vaccinated (CoV-T1; left) and SARS-CoV-2-recovered patient (CoV-T2; right). We found that SARS-CoV-2-specific CD21CD27+ activated Bm cells and CD21CD27 Bm cells were the predominant subsets in circulation during acute infection and upon vaccination. Nat. Making statements based on opinion; back them up with references or personal experience. Compared with their circulating counterparts, tonsillar S+ and N+ Bm cells expressed, on average, more CD69, less Ki-67, reduced T-bet and several chemokine receptors differently (Fig. ; #323530-177975 to S.A.; #323530-191220 to C.C. Nature 584, 437442 (2020). ## [97] compiler_4.2.0 plotly_4.10.1 png_0.1-8 Biotechnol. In tonsils, the S+ Bm cells were less IgG+ (77.4% versus 82.1%) and IgM+ (2.4% versus 5.5%), but more IgA+ (9.1% versus 6%) compared with the circulation (Fig. We recruited 11 healthy controls (Extended Data Fig. Looking for job perks? 1e,f). 4a,c). PubMed O.B. As cell identity is only available after intergration and clustering? 2c), and S+ Bm cells underwent strong proliferation during the acute phase (Fig. Red dashed lines indicate minimal and maximal cumulative enrichment values. ## [46] scales_1.2.1 mvtnorm_1.1-3 spatstat.random_3.1-3 1c and Supplementary Table 4) with no history of SARS-CoV-2 infection and seronegative for SARS-CoV-2 S S1-specific antibodies. Content Discovery initiative April 13 update: Related questions using a Review our technical responses for the 2023 Developer Survey, Remove rows in a dataframe containing values outside multiple intervals. All samples were analyzed by flow cytometry, and paired week 2, month 6 post-second dose and week 2 post-third dose samples from three patients were additionally assessed by scRNA-seq. Colors indicate Bm cell subsets. 22,54). Koutsakos, M. et al. Lines connect samples of same individual. Rev. Each set of modal data (eg. ), Clinical Research Priority Program CYTIMM-Z of University of Zurich (UZH) (to O.B. original object. Find centralized, trusted content and collaborate around the technologies you use most. However, this brings the cost of flexibility. ## [49] miniUI_0.1.1.1 Rcpp_1.0.10 plotrix_3.8-2 J. Immunol. Upon antigen reencounter, Bm cells differentiate into antibody-secreting plasma cells or reenter GCs where they undergo additional SHM9. ## [76] cachem_1.0.7 cli_3.6.0 generics_0.1.3 The frequency of blood S+ Bm cells was approximately fivefold increased post-vaccination at month 12 compared with pre-vaccination at month 6 post-infection (Fig. Rodda, L. B. et al. For each gene, evaluates (using AUC) a classifier built on that gene alone, to classify between two groups of cells. contributed to patient recruitment and clinical management. Each dot represents an individual (n=6). Use MathJax to format equations. Hi @attal-kush , However, the differentiation path of CD21CD27+ Bm cells and CD21CD27 Bm cells remains ill-defined. But I'm also curious how others approach this! a, SARS-CoV-2-infected patients were analyzed by spectral flow cytometry and scRNA-seq at acute infection and months 6 and 12 post-infection. 8g). accept.value = NULL, How to create a virtual ISO file from /dev/sr0, Adding EV Charger (100A) in secondary panel (100A) fed off main (200A), English version of Russian proverb "The hedgehogs got pricked, cried, but continued to eat the cactus". Can the game be left in an invalid state if all state-based actions are replaced? 8e,f). ), Forschungskredit Candoc grant from UZH (FK-20-022; to S.A.), Young Talents in Clinical Research program of the SAMW and G. & J. Bangerter-Rhyner Foundation (YTCR 08/20; to M.E.R. Sci. ## [121] R6_2.5.1 promises_1.2.0.1 KernSmooth_2.23-20 Asterisks indicate significantly different segment usage between S and the respective S+ Bm cell subsets. :) Thank you. ## [34] jsonlite_1.8.4 progressr_0.13.0 spatstat.data_3.0-0 ## [3] patchwork_1.1.2 thp1.eccite.SeuratData_3.1.5 The flow cytometry and scRNA-seq subcohort characteristics are presented in Supplementary Tables 1 and 2, respectively. Creates a Seurat object containing only a subset of the cells in the Neutrophils and emergency granulopoiesis drive immune suppression and All samples were analyzed by flow cytometry and paired blood and tonsil samples from four patients also by scRNA-seq. 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. 10, eaan8405 (2018). Which was the first Sci-Fi story to predict obnoxious "robo calls"? Samples in f were compared using two-proportions z-test. Proc. Extended Data Fig. The code generated during the current study is available at https://github.com/Moors-Code/MBC_Plasticity_Moor_Boyman_Collaboration. Cyster, J. G. & Allen, C. D. C. B cell responses: cell interaction dynamics and decisions. Setliff, I. et al. Gene sets were obtained from the Molecular Signatures Database (v7.5.1, collections H and C5) and loaded in R by the package msigdbr (v.7.5.1). Flow cytometry analysis of S+ Bm cells showed an upregulation of Blimp-1 at week 2 post-second dose compared with month 6, and increased expression of T-bet, FcRL5, CD71 and Ki-67 at week 2 post-second dose and post-third dose (Extended Data Fig. Lung-resident memory B cells established after pulmonary influenza infection display distinct transcriptional and phenotypic profiles. Use the Previous and Next buttons to navigate the slides or the slide controller buttons at the end to navigate through each slide. At this point the tutorial displayed the UMAP plots with DimPlots and went forward to combine additional human PBMC datasets from eight different technologies. 36, 421427 (2018). ISSN 1529-2916 (online) Clustering was performed using the Louvain algorithm and a resolution of 0.4. Efficient recall of Omicron-reactive B cell memory after a third dose of SARS-CoV-2 mRNA vaccine. Content Discovery initiative April 13 update: Related questions using a Review our technical responses for the 2023 Developer Survey, R: subsetting data frame by both certain column names (as a variable) and field values. Chang, L. Y., Li, Y. This study was approved by the Cantonal Ethics Committee of Zurich (BASEC #2016-01440). The transient occurrence of vaccine-specific CD21CD27 Bm cells has been described during responses to the influenza vaccine12,20, with one study reporting this Bm cell subset in de novo rather than recall responses20. and A.E.M. 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. Tonsils were processed according to established protocols47,53. This work was funded by the Swiss National Science Foundation (#4078P0-198431 to O.B. To subscribe to this RSS feed, copy and paste this URL into your RSS reader. Article Immunol. I did SCTransform() workflow, then subset a cluster of interest. White areas represent BCR sequences found in single cells only. Viant, C. et al. ## 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. Holla, P. et al. Developed by Paul Hoffman, Satija Lab and Collaborators. IFI6 and ISG15, on the other hand, are core interferon response genes and are upregulated accordingly in all cell types. 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? I have similar questions as @attal-kush with regards to reclustering of a subset of an integrated object. At month 6 post-infection (pre-vaccination), 80% of those 30 clones had a CD21+ resting Bm cell phenotype (Fig. Sci. 1d). seurat_subset <- SubsetData (seurat_object, subset.name = neuron_ids [1], accept.low = 0.1) However, I want to subset on multiple genes. Lines connect samples of same individual. I wonder if anyone has found a definitive answer for this? Human T-bet governs the generation of a distinct subset of CD11chighCD21low B cells. ## attached base packages: Gowans, J. L. & Uhr, J. W. The carriage of immunological memory by small lymphocytes in the rat. It seems that a repeated possibility would be to change the features.to.integrate argument in IntegrateData to all_common_features between the different integrated datasets, however I have a quite big dataset (100.000 cells) and I'm experiencing memory issues: In any case, could this workflow (slightly modified from the one from @attal-kush) be accepted to subcluster from an integrated object? First the following steps were performed in the order that they were displayed: SCTransform, SelectIntegrationFeatures, PrepSCTIntegration, FindIntegrationAnchors, IntegrateData, RunPCA and RunUMAP. Thanks for contributing an answer to Bioinformatics Stack Exchange! In e, two-sided Wilcoxon test was used with Holm multiple comparison correction. 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 assume if I just need to delete the 3 lines of code I just mentioned above and change Gene expression markers of identity classes FindMarkers Seurat The expansion of human T-bet high CD21 low B cells is T cell dependent. | WhichCells(object = object, ident = "ident.keep") | WhichCells(object = object, idents = "ident.keep") | Primary Handling Editor: Ioana Visan in collaboration with the Nature Immunology team. then the answer is to run it on the integrated assay). Immunity 54, 12901303.e7 (2021). In e, two-sided Wilcoxon rank sum test was used and P values corrected by Bonferroni correction. 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. Browse other questions tagged, Where developers & technologists share private knowledge with coworkers, Reach developers & technologists worldwide. Identified Bm cells (SARS-CoV-2 S B cells, n=2258; SWT+ Bm cells, n=1298) were subsequently reclustered as indicated in the box. Why did US v. Assange skip the court of appeal? Samples were stained as described for spectral flow cytometry using biotinylated SWT, RBD, Sbeta and Sdelta (MiltenyiBiotec) and hemagglutinin (SinoBiological) that were multimerized at 4:1 molar ratios with fluorescently labeled and/or barcoded SAV (TotalSeqC, BioLegend). control_subset <- RunUMAP(control_subset, dims = 1:15) ## [61] ellipsis_0.3.2 ica_1.0-3 farver_2.1.1 I have also been working on the single cell dataset and there are several times that i need to subcluster a proportion cell type. Choose a subset of cells, and then split by samples and then re-run the integration steps (select integration features, find anchors and integrate data). Did the Golden Gate Bridge 'flatten' under the weight of 300,000 people in 1987? Antigen-specific cells per sample were sorted with 1,5002,000 nonspecific B cells, as shown in Extended Data Figs. I hope it is useful. In the meantime, to ensure continued support, we are displaying the site without styles Gene set variation and enrichment analysis revealed a strong enrichment of a previously described B cell signature of IgDCD27CXCR5 atypical Bm cells from patients with systemic lupus erythematosus (SLE)36, in our SARS-CoV-2-specific CD21CD27FcRL5+ Bm cell subset (Fig. | RotatedAxis | Rotates x-axis labels |. 5a,b and Extended Data Fig. First, we focused on samples from nonvaccinated individuals at acute infection (n=59, day 14 on average after symptom onset), month 6 (n=61, day 202 after symptom onset) and month 12 (n=17, day 374) (Fig. subset.name = NULL, ## [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C From reading the other issues posted regarding the topic it appears that any kind of re-analysis prior to integration is not recommended, and that once subsetted a integrated data set should just be re-scaled and the pipeline followed on from this point on. subsetting cells to find sub clusters - Github 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. P values are shown if significant (p<0.05). Frauke Muecksch, Zijun Wang, Michel C. Nussenzweig, R. Camille Brewer, Nitya S. Ramadoss, Tobias V. Lanz, Laila Shehata, Wendy F. Wieland-Alter, Laura M. Walker, Alice Cho, Frauke Muecksch, Michel C. Nussenzweig, Marios Koutsakos, Patricia T. Illing, Katherine Kedzierska, Anastasia A. Minervina, Mikhail V. Pogorelyy, Paul G. Thomas, Nature Immunology 64). | ----------- | ----------- | Samples were acquired on a Cytek Aurora cytometer using the SpectroFlo software. We obtained paired tonsil and peripheral blood mononuclear cell and serum samples. M.E.R. As an aside, your middle two samples with a majority portion of cells with %mitochondrial reads > 10% are rather worrying, as they may largely be dead/dying. 6, eabh0891 (2021). 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. I have been subsetting a cluster from a Seurat object to find subclusters. 7g). T-bet+ B cells are induced by human viral infections and dominate the HIV gp140 response. | RenameIdent(object = object, old.ident.name = "old.ident", new.ident.name = "new.ident") | RenameIdents(object = object, "old.ident" = "new.ident") | Gene set variation analysis with the package gsva (v1.42.0) was used to estimate gene set enrichments for more than two groups61. Generally, you'll want use different parameters for each sample. ), BRCCH-EDCTP COVID-19 initiative (to A.E.M.) Any argument that can be retreived Functional groups of genes were ordered by hierarchical clustering. The standard Seurat workflow takes raw single-cell expression data and aims to find clusters within the data. Does anyone has found a better solution to re-project a cluster of the dataset? Increased memory B cell potency and breadth after a SARS-CoV-2 mRNA boost, BNT162b2 vaccine induces divergent B cell responses to SARS-CoV-2 S1 and S2, Systematic comparison of respiratory syncytial virus-induced memory B cell responses in two anatomical compartments, Single-cell epigenomic landscape of peripheral immune cells reveals establishment of trained immunity in individuals convalescing from COVID-19, The germinal centre B cell response to SARS-CoV-2, Anti-SARS-CoV-2 receptor-binding domain antibody evolution after mRNA vaccination, Human CD8+ T cell cross-reactivity across influenza A, B and C viruses, SARS-CoV-2 antigen exposure history shapes phenotypes and specificity of memory CD8+ T cells, Signature of long-lived memory CD8+ T cells in acute SARS-CoV-2 infection, https://github.com/Moors-Code/MBC_Plasticity_Moor_Boyman_Collaboration. I used the first way as @Zha0rong described for re-clustering of subset cells, choosing a subset and then use the integration assay to Run PCA, umap, findneighbors and findclusters to do subclustering. | WhichCells(object = object, subset.name = "name", low.threshold = low, high.threshold = high) | WhichCells(object = object, expression = name > low & name < high) | Heat maps were generated using the ComplexHeatmap package (v2.13.1) or pheatmap package (v1.0.12) (ref. b, Distribution of S+ Bm cell subsets in persistent and newly detected clones is shown at indicated timepoints. We used a two-tailed Wilcoxon matched-pairs signed-rank test in b, d and g, and two-sided Wilcoxon test in e. The HolmBonferroni method was used for P value adjustment of multiple comparisons. Troubleshooting why subsetting of spatial object does not work, Automatic subsetting of a dataframe on the basis of a prediction matrix, transpose and rename dataframes in a for() loop in r. Unexpected uint64 behaviour 0xFFFF'FFFF'FFFF'FFFF - 1 = 0? The transcription factors ZEB2 and T-bet cooperate to program cytotoxic T cell terminal differentiation in response to LCMV viral infection. BCR diversity was slightly reduced in S+ CD21CD27FcRL5+ compared with S+ CD21+ resting Bm cells (Extended Data Fig. Now I understand that batch variation is a pain in the a** but honestly one has to assume this will occur naturally in a PCR as well. Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article. The sample code is also provided at the end. B, WNNUMAP analysis of Bm cells from COVID-19 patients is provided at months 6 and 12 post-infection, colored by clustering based on single-cell transcriptome and cell surface protein levels (left) and by indicated surface protein markers (right). CAS Another useful way to visualize these changes in gene expression is with the split.by option to the FeaturePlot() or VlnPlot() function. Looking for job perks? CD21+ resting Bm cells became prevalent at 612months post-infection. The images or other third party material in this article are included in the articles Creative Commons license, unless indicated otherwise in a credit line to the material. 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. Sci. 9, 47 (2020). I did see batch effects here (cells from different batches did not share clusters). and JavaScript. control_subset <- ScaleData(control_subset, verbose = FALSE, vars.to.regress = c( "percent.mt")) By clicking Accept all cookies, you agree Stack Exchange can store cookies on your device and disclose information in accordance with our Cookie Policy. 56), with k set to 20, the following B cell markers were used: CD11c, CD19, CD20, CD21, CD24, CD27, CD38, CD71, CD80, CXCR5, BAFF-R, FcRL5, IgA, IgD, IgG, IgM, Blimp1, IRF8, Ki67 and Tbet. ## [7] splines_4.2.0 listenv_0.9.0 scattermore_0.8 These observations in circulating Bm cells were paralleled by the appearance of resting Bm cells in tonsils, where they showed high expression of CD69 and CD21 and comparable SHM counts to circulating Bm cells. For scRNA-seq data, distribution was assumed to be normal, but this was not formally tested. Extended Data Fig. All plotting functions will return a ggplot2 plot by default, allowing easy customization with ggplot2. This process consists of data normalization and variable feature selection, data scaling, a PCA on variable features, construction of a shared-nearest-neighbors graph, and clustering using a modularity optimizer. limma powers differential expression analyses for RNA-sequencing and microarray studies. 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. 16 patients undergoing tonsillectomies for unrelated conditions were included and paired blood and tonsil samples obtained. Naradikian, M. S., Hao, Y. Note that plotting functions now return ggplot2 objects, so you can add themes, titles, and, "2,700 PBMCs clustered using Seurat and viewed\non a two-dimensional tSNE", # Plotting helper functions work with ggplot2-based scatter plots, such as DimPlot, FeaturePlot, CellScatter, and. batch effect correction), and to perform comparative scRNA-seq analysis of across experimental conditions. Sign up for the Nature Briefing newsletter what matters in science, free to your inbox daily. PubMedGoogle Scholar. 6b), whereas at month 12 post-infection (post-vaccination) 32% of persistent Bm clones showed a CD21CD27+CD71+ and 28% a CD21CD27FcRL5+ Bm cell phenotype. Downstream analysis was conducted in R version 4.1.0 mainly with the package Seurat (v4.1.1) (ref. # Lastly, we observed poor enrichments for CCR5, CCR7, and CD10 - and therefore remove them from the matrix (optional), "~/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, # Note that plotting functions now return ggplot2 objects, so you can add themes, titles, and options onto them, '2,700 PBMCs clustered using Seurat and viewed\non a two-dimensional tSNE', # Plotting helper functions work with ggplot2-based scatter plots, such as DimPlot, FeaturePlot, CellScatter, and FeatureScatter, # 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, satijalab/seurat: Tools for Single Cell Genomics.
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