Tag: UMAP

Human fetal cerebellar cell atlas informs medulloblastoma origin and oncogenesis

Wang, J., Garancher, A., Ramaswamy, V. & Wechsler-Reya, R. J. Medulloblastoma: from molecular subgroups to molecular targeted therapies. Annu. Rev. Neurosci. 41, 207–232 (2018). Article  CAS  PubMed  Google Scholar  Cavalli, F. M. G. et al. Intertumoral heterogeneity within medulloblastoma subgroups. Cancer Cell 31, 737–754.e736 (2017). Article  CAS  PubMed  PubMed Central …

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Multi-level cellular and functional annotation of single-cell transcriptomes using scPipeline

Software Figure preparation: CorelDRAW x8 (Corel); Bioinformatic analyses: R v 4.0.3 (R Foundation for Statistical Computing). Computational resources Analyses were run on a desktop computer with an Intel Core i9-10900L CPU (3.70 GHz, 10 cores, 20 threads) with 120 GB RAM running Windows 10 Pro (v21H2). Data preprocessing scRNA-seq data sets…

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Identification of unique DNA methylation sites in Kabuki syndrome using whole genome bisulfite sequencing and targeted hybridization capture followed by enzymatic methylation sequencing

Niikawa N, Matsuura N, Fukushima Y, Ohsawa T, Kajii T. Kabuki make-up syndrome: a syndrome of mentalretardation, unusual facies, large and protruding ears, and postnatal growth deficiency. J Pediatrics. 1981;99:565–9. CAS  Article  Google Scholar  Kuroki Y, Suzuki Y, Chyo H, Hata A, Matsui I. A new malformation syndrome of long…

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Low expression of key transcripts in scRNAseq dataset after deeper sequencing

Low expression of key transcripts in scRNAseq dataset after deeper sequencing 1 I am having an issue with my single cell data set. This alert was shown after I requested additional reads per cell to be incorporated with the initial data we received. We have previously performed single cell on…

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Subtype and cell type specific expression of lncRNAs provide insight into breast cancer

lncRNA expression according to breast cancer clinicopathological subtypes To identify lncRNAs expressed by specific breast cancer subtypes or associated with clinicopathological features, we analyzed RNA-sequencing data from two large independent breast cancer cohorts: SCAN-B (n = 3455)17 and TCGA-BRCA (n = 1095). We focused on lncRNAs annotated in the Ensembl18 v93 non-coding reference transcriptome…

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Single-cell analyses define a continuum of cell state and composition changes in the malignant transformation of polyps to colorectal cancer

Mapping molecular changes across malignant transformation We generated single-cell data for 81 samples collected from eight FAP and seven non-FAP donors (Fig. 1a and Supplementary Tables 1 and 2). For each tissue, we performed matched scATAC-seq and snRNA-seq (10x Genomics). We obtained high-quality single-cell chromatin accessibility profiles for 447,829 cells…

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GeneActivity without Fragments file in Seurat for Integrating scRNA-seq and scATAC-seq

Hi all, I am new to R and Seurat, and I am following Seurat tutorials to find anchors between RNA-seq and ATAC-seq data according to: Combining the two tutorials is difficult for a cell line data set I am using for SNARE-seq Human here. I managed to run the following…

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scRNAseq analysis – h5ad file conversion to Seurat format

scRNAseq analysis – h5ad file conversion to Seurat format 0 Hi all. I have a single .h5ad file that contains scRNAseq data from several samples. I would like to convert it so that I can open it in Seurat (I am comfortable with R, but not with Python). I have…

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dataframe – uwot is throwing an error running the Monocle3 R package’s “find_gene_module()” function, likely as an issue with how my data is formatted

I am trying to run the Monocle3 function find_gene_modules() on a cell_data_set (cds) but am getting a variety of errors in this. I have not had any other issues before this. I am working with an imported Seurat object. My first error came back stating that the number of rows…

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Why do UMAP on all scRNA-seq samples rather than a UMAP for each treatment?

Why do UMAP on all scRNA-seq samples rather than a UMAP for each treatment? 1 When analyzing scRNA-seq data, why do people pool all their data across treatments and run UMAP on the combined dataset rather than running a separate UMAP on each treatment group? For example, say you’re looking…

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Novel diagnostic biomarkers for keloid based on GEO database

Introduction Keloid is excessive fibrosis of the skin that extends beyond the area of injury and does not regress.1 Keloid can occur in the joints and mouth after several years of severe injury, including burns, chemical injury, wound, and surgical incision.2 Keloids on the joints affect the quality of life,…

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Identification of a regulatory pathway inhibiting adipogenesis via RSPO2

Integration of APC scRNA-seq data reveals heterogeneity of adipocyte progenitor cells In a previous study9, we defined Lin−Sca1+CD142+ APCs as adipogenesis regulatory (Areg) cells and demonstrated that these cells are both refractory toward adipogenesis and control adipocyte formation of APCs through paracrine signaling. In contrast, Merrick et. al.4 observed that Lin−CD142+ cells…

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Integrating Bulk RNA-seq data with Single cell RNA seq data

Integrating Bulk RNA-seq data with Single cell RNA seq data 0 Hello all, recently, I had been trying to integrate bulk RNAseq data into single-cell data where I treat each sample in my bulk RNAseq data as a single cell and integrate it into the single-cell data based on the…

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Adding numbers and characters to legend key in ggplot2 of UMAP clusters

Adding numbers and characters to legend key in ggplot2 of UMAP clusters 0 Hi everyone, I have a UMAP cluster, however there are so many clusters that the descriptions look clunky if i put them on the umap…but then there are too many colors if it just colors. So, i…

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Non-genetic determinants of malignant clonal fitness at single-cell resolution

1. Turajlic, S., Sottoriva, A., Graham, T. & Swanton, C. Resolving genetic heterogeneity in cancer. Nat. Rev. Genet. 20, 404–416 (2019). CAS  PubMed  Google Scholar  2. Marine, J. C., Dawson, S. J. & Dawson, M. A. Non-genetic mechanisms of therapeutic resistance in cancer. Nat. Rev. Cancer 20, 743–756 (2020). CAS …

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tSNE and UMAP of scATAC-seq data looks like spaghetti

tSNE and UMAP of scATAC-seq data looks like spaghetti 0 I would like to use R to generate cluster my 20k cells from a single cell ATAC-seq experiment. I ran PCA then selected the first 50 components, which were put into tSNE’s normalize_input() then Rtsne(). This is the result I…

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Correct usage of FindConservedMarkers() in Seurat

Correct usage of FindConservedMarkers() in Seurat 0 Dear all, I have a Seurat object of a certain cell type with a UMAP of 7 clusters. I also have information about the sample’s origin (primary tumor/metastatic) in my metadata. Looking at the UMAP I can clearly see that clusters 1 and…

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Bioconductor – GEOexplorer (development version)

DOI: 10.18129/B9.bioc.GEOexplorer     This is the development version of GEOexplorer; to use it, please install the devel version of Bioconductor. GEOexplorer: an R/Bioconductor package for gene expression analysis and visualisation Bioconductor version: Development (3.14) GEOexplorer is a Shiny app that enables exploratory data analysis and differential gene expression of…

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WNN in Seurat

Dear all, I am trying to follow the WNN vignette here satijalab.org/seurat/articles/weighted_nearest_neighbor_analysis.html After the steps below, I would like to annotate my clusters, hence I need to know the markers which best represent each cluster. pbmc <- FindMultiModalNeighbors(pbmc, reduction.list = list(“pca”, “lsi”), dims.list = list(1:50, 2:50)) pbmc <- RunUMAP(pbmc, nn.name

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The Biostar Herald for Friday, September 03, 2021

The Biostar Herald publishes user submitted links of bioinformatics relevance. It aims to provide a summary of interesting and relevant information you may have missed. You too can submit links here. This edition of the Herald was brought to you by contribution from zx8754, Istvan Albert, and was edited by…

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A question about scRNA-seq analysis

A question about scRNA-seq analysis 0 Dear all, please may I ask for a suggestion : I have a scRNA-seq dataset, which has 2 groups (Control and Model). I would like to process all the samples into cluster by tSNE or UMAP , then classification or differentiation the cell types….

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Best compression for single cell RNA-seq object

Best compression for single cell RNA-seq object 0 I generated a scRNA-seq object (counts, PCA, UMAP embeddings, DEGs etc.) in Scanpy or Seurat. What is the best data structure to store this in to reduce the size of the object? I’m considering H5AD (scanpy/anndata), RDS or H5Seurat (Seurat), or Loom…

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WNN (Seurat v4) vs. totalVI (scvi-tools) for CITE-seq data

WNN (Seurat v4) vs. totalVI (scvi-tools) for CITE-seq data 0 I want to build a UMAP from CITE-seq data with a joint embedding of the scRNA-seq and protein ab data. What’s the ‘best’ method in terms of representing the most accurate embedding? In the totalVI paper, they say totalVI >…

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How to transform the deg gene list from seurat to a gene list input to clusterProfiler compareCluster ?

Sorry for lateness, I wanted to do something similar. This is what I did for reference: Using a Seurat generated gene list for input into ClusterProfiler to see the GO or KEGG terms per cluster. I’ll keep the meat and potatoes of the Seurat vignette in this tutorial: library(dplyr) library(Seurat)…

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VisCello Shiny app code for hosting snRNA-seq data

I am trying to set up VisCello shiny app for hosting some of our single cell data, analyzed in Seurat: github.com/qinzhu/VisCello I am using the following code though running into a problem, the app launches however I dont see the umaps and when I click over to differential expression the…

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UMAP of TRA/B

Hello, I have output from a single cell sequencing run that has both the VDJ and gene expression data. For the same cells, we also used a hybrid capture approach to sequence the TCR sequences. I have compared the TCR sequences across the two approaches and I have found a…

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UMAP vs “rigorous” t-SNE

UMAP vs “rigorous” t-SNE 1 I’ve heard a lot of people discussing UMAP recently as though it has essentially superseded t-SNE for visualizing scRNA-seq data. UMAP is certainly impressive, but it seems to me that there are a lot of things one can do to pretty dramatically improve the output…

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Experience with Cytobank

Experience with Cytobank 0 Dear all We are medical doctors and immunologists working with 16 color phenotype FCS files created on patient blood PBMC samples. We would like to independently work with a clustering algorithm that is intuitive and easy to manage. We have been exploring Cytobank briefly but we…

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Can someone explain the differences between various 1000 genome project and gnomad call sets? Also any straightforward PCA implementation on them?

I’ve been trying to delve into the data from whole genome sequencing, specifically by looking at the already existing data in the 1000 genome project and gnomad, and I have a lot of questions. Does gnomAD contain the 1000gp samples? I’ve found many vcf including these: ftp.1000genomes.ebi.ac.uk/vol1/ftp/release/20130502/supporting/hd_genotype_chip/ ftp.1000genomes.ebi.ac.uk/vol1/ftp/phase3/integrated_sv_map/ ftp.1000genomes.ebi.ac.uk/vol1/ftp/phase1/analysis_results/integrated_call_sets/ gnomad.broadinstitute.org/downloads…

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Corelate TCR data to clusters/GEX/CITEseq data

Corelate TCR data to clusters/GEX/CITEseq data 1 Hello everyone, I just added my TCR VDJ data as metadata to my Seurat object (as described in the tutorial here). So, I basically ended up with two different collumns of metadata where my barcodes are assigned to the clonotypes and the cdr3…

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