Cannot find layers in this seurat object
WebAn optional Seurat object; if passes, will return an object with the identities of selected cells set to ident. ident. An optional new identity class to assign the selected cells... Ignored. … WebNov 9, 2024 · New issue No seurat_annotation in seurat Object for my data #5285 Closed Aya-Balbaa opened this issue on Nov 9, 2024 · 2 comments Aya-Balbaa on Nov 9, 2024 timoast completed on Nov 12, 2024 Sign up for free to join this conversation on GitHub . Already have an account? Sign in to comment
Cannot find layers in this seurat object
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WebJul 7, 2024 · 1. I have a Seurat object of 8 patients. I want to add metadata to that so that I have origin of each cell. At the moment UMAP just shows a bunch of cells while I want to … WebDefines S4 classes for single-cell genomic data and associated information, such as dimensionality reduction embeddings, nearest-neighbor graphs, and spatially-resolved …
WebSaving a dataset. Saving a Seurat object to an h5Seurat file is a fairly painless process. All assays, dimensional reductions, spatial images, and nearest-neighbor graphs are … WebJul 19, 2024 · Hello every one! I have 10X Genomics output from multiple runs. From each run, I created a Seurat Object from the output/filtered_gene_bc_matrices/ folders and then merged them into 1 seurat object.. I used the above merged object for all my clustering analysis and have exported this all as an RDS file.
Weblabels. A vector of labels for the points; if NULL, will use rownames of the data provided to the plot at the points selected. repel. Use geom_text_repel to create a nicely-repelled labels; this is slow when a lot of points are being plotted. If using repel, set xnudge and ynudge to 0. xnudge, ynudge. Amount to nudge X and Y coordinates of ... WebJun 13, 2024 · Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
WebJun 19, 2024 · Maybe you can try Seurat::AddModuleScore (), then FeaturePlot () and see if some of your B cells are different. After plotting this on GenePlot (), perhaps you can set a cutoff, then assign identities. Alternatively, use your B cell gene list in RunPCA (object, pc.genes = yourgenelist) instead of the usual variable genes.
WebJul 2, 2024 · NA in the sparseMatrix after using log normalization. Then when I used , it created a lot of zeros. I guess when feeded this scaled data to , removed columns/rows having variance = 0 and the final matrix was smaller than their expected number of left/right singular vectors. Fyi, this is my data (a Seurat object). : cane base tipsWebAug 16, 2024 · Help with error: Cannot find 'Group' in this Seurat object #4 Open sjspielman opened this issue on Aug 16, 2024 · 4 comments on Aug 16, 2024 Sign up for free to join this conversation on GitHub . Already have an account? Sign in to comment Assignees No one assigned Labels None yet Projects None yet Milestone No milestone … fiskars paper cutter for scrapbookingWebDec 18, 2024 · Error: Cannot find 'umap' in this Seurat object. I have tried renaming and reinstalling umap-learn with reticulate::py_install(packages = 'umap-learn') however this isn't working, I am using python version 3.8, … cane badgesWebThe concept of global objects in Seurat is designed as an extension to the assay-centric nature of objects. In Seurat, each assay is considered to be one experiment or measurement of data for a common group of cells. These assays are then used to generate working summaries, such as reduced dimension space or nearest-neighbor graphs. cane back rocking chairs pictureWebNew data visualization methods in v3.0 - Satija Lab fiskars pinking shearsWebOct 27, 2024 · I am grateful if someone could help using csv file to load the UMAP/tSNE coordinate from Seurat object (rds file) to the anndata object (adata) in python. I used a stupid way but it worked: 1- save the rds file to loom file. 2- read the loom file: adataTemp = scv.read('seurat.loom') 3- put the umap back to adata: cane bamboo laundry basketWebTo add the metadata i used the following commands. First I extracted the cell names from the Seurat object. > Cells <- WhichCells (seurat_object) Then I created a list of the morphologically determined cell types using numbers 1-3 this NOTE: the list is much longer but abbreviated as the first 3 here. > MorphCellTypes = c (1,2,3) cane back settee