Tag: UMAP

PCA from plink2 for SGDP using a pangenome and DeepVariant

Hi there, I’m doing my first experiments with PCA and UMAP as dimensionality reductions to visualize a dataset I’ve been working on. Basically, I used the samples from the SGDP which I then mapped on the human pangenome for, finally, calling small variants with DeepVariant. I moved on with some…

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Unravelling cell type-specific responses to Parkinson’s Disease at single cell resolution | Molecular Neurodegeneration

Single nucleus RNA-seq reveals cell type heterogeneity in human SNpc We sampled SNpc from post-mortem human brains of 15 sporadic Parkinson’s disease (PD) patients and 14 Control individuals (see Supplementary Table 1 for full pathology reports). Using a 10X Genomics Chromium platform, we performed single nucleus RNA-seq (snRNA-seq) on more than…

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Condition specific marker detection and problem with the distribution of cells from different samples

Condition specific marker detection and problem with the distribution of cells from different samples 1 I have 6 scRNAseq samples and made a umap using all cells from all 6 samples and in the UMAP every sample has a different color (in total 6 colors) and the goal was to…

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Study uncovers unique genetic diversity in Australian Indigenous populations

Scientists at the Australian National University (ANU) have comprehensively analyzed the genomes of Australian Indigenous communities and found a rich genetic diversity. Their study is published in the journal Nature. Study: Indigenous Australian genomes show deep structure and rich novel variation. Image Credit: ChameleonsEye / Shutterstock Background Genetic structures of Australian Indigenous…

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Highly dynamic inflammatory and excitability transcriptional profiles in hippocampal CA1 following status epilepticus

Dynamic mRNA signatures in the early phase of epileptogenesis after Pilocarpine-induced SE To decipher transcriptional changes early after pilocarpine-induced SE in the hippocampal CA1 subfield, we compared mRNA expression profiles of pilocarpine-induced SE animals and non-SE controls in hippocampal CA1 at five different time points, i.e. 6, 12, 24, 36…

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Indigenous Australian genomes show deep structure and rich novel variation

Inclusion and ethics The DNA samples analysed in this project form part of a collection of biospecimens, including historically collected samples, maintained under Indigenous governance by the NCIG11 at the John Curtin School of Medical Research at the Australian National University (ANU). NCIG, a statutory body within ANU, was founded…

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How to remove center population from seurat cluster

How to remove center population from seurat cluster 0 Dear all, apologize for many posts. I have done my clustering, but there is weird tidy population (in red circle) that is not stay close to its assigned cluster (kindly see attach). In the attached imaged, that cluster has been assigned…

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JoinLayers function for Seurat Object for annotation with SingleR

Dear all, I have the following issue: I have a Seurat object with 7 layers of raw gene expression counts for 7 different patients. In order to annotate the object with SingleR I have now used the function “JoinLayers” to combine all counts into one layer of counts of all…

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Can’t do runPCA after merging a splited Seurat object before UMAP

Hi everyone, When I started my analysis, I merged 3 samples. merged_seurat <- merge(x = PC9_1_raw_feature_bc_matrix, y = c(PC9_2_raw_feature_bc_matrix, PC9_3_raw_feature_bc_matrix), add.cell.id = c(“PC9_1”, “PC9_2”, “PC9_3”)) After cell filtering, I checked the cell cycle and batch effects (no batch effect, I won’t do integration). I split my Seurat object to do…

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University of Connecticut Single Cell RNA-seq Workshop December 12-15, 2023

News:University of Connecticut Single Cell RNA-seq Workshop December 12-15, 2023 0 Join UConn’s Computational Biology Core for a Single Cell RNAseq Workshop December 12-15, 2023 Scope of the workshop: Introduction to different data file formats. Understanding the Considerations while designing single-cell RNA-seq experiments, Hands on steps to convert raw single-cell…

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GEO dataset Microarray data analysis help

Hello Everyone , I am new to microarray dataset . I want to do this similar kind of plotting using this same mentioned dataset for a different gene . GEO ID : GSE76008 I have tried GEO2R script : <h6>#</h6> library(GEOquery) library(limma) library(umap) gset <- getGEO(“GSE76008”, GSEMatrix =TRUE, AnnotGPL=TRUE)[1] fvarLabels(gset)…

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scVelo cell transitions from marker gene expressing cells

scVelo cell transitions from marker gene expressing cells 0 Hi Im working with scVelo and looking to match a subset of cells in one cluster with preferential cell state transitions and what gene(s) may underlie this connection. Currently we can do the following to put in specific cells from adata…

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After merging batches, I got very segmented umap in scanpy

After merging batches, I got very segmented umap in scanpy 0 I merged four samples of 10X genomics and I did batch correction using harmony which converged after 4 iterations. I get this very segmented umap. But If I do each sample separately I get a normal clustering with (~28…

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Single-cell RNAseq analysis of spinal locomotor circuitry in larval zebrafish

. 2023 Nov 17:12:RP89338. doi: 10.7554/eLife.89338. Affiliations Expand Affiliation 1 Vollum Institute, Oregon Health & Science University, Portland, United States. Item in Clipboard Jimmy J Kelly et al. Elife. 2023. Show details Display options Display options Format AbstractPubMedPMID . 2023 Nov 17:12:RP89338. doi: 10.7554/eLife.89338. Affiliation 1 Vollum Institute, Oregon Health &…

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UMAP or TSNE for single cells?

UMAP or TSNE for single cells? 0 Dear all fellow, I am just slowly getting into single cells. I have been working with my data for 2.5 months now and tried to learn all the tips about single cell good practices. I personally find UMAP is tricky especially when we…

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fastest UMAP method

fastest UMAP method 5 I am trying to generate a Uniform Manifold Approximation and Projection (UMAP) for about 300,000 observations of 36 variables. So far I have been using the umap package in R but this seems prohibitively slow (for exploratory analyses and parameter optimisation). Can someone recommend an alternative…

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The effects of methylphenidate and atomoxetine on Drosophila brain at single-cell resolution and potential drug repurposing for ADHD treatment

Both MPH and ATX increase the locomotor activity of wild-type Drosophila To investigate the cell type-specific molecular mechanisms of ADHD drugs in the brain at single-cell resolution, we conducted behavioral experiments and scRNASEQ in wild-type (WT) adult male Drosophila melanogaster following exposure to MPH, ATX, and control treatment. Here, we…

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Bioconductor – scDesign3

DOI: 10.18129/B9.bioc.scDesign3   A unified framework of realistic in silico data generation and statistical model inference for single-cell and spatial omics Bioconductor version: Release (3.18) We present a statistical simulator, scDesign3, to generate realistic single-cell and spatial omics data, including various cell states, experimental designs, and feature modalities, by learning…

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Single-cell RNA sequencing reveals a molecular blueprint of circuits governing locomotor speed

Researchers at Karolinska Institutet, Sweden have uncovered the molecular logic underpinning the assembly of spinal circuits that control the speed of locomotion in adult zebrafish. The study has recently been published in Nature Neuroscience. What does the study show? A fundamental hallmark of motor actions is the flexibility of their…

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running for loop for resolution of seurat got error: Error: Not an S4 object.

Dear All fellows, I’m using SCTtransform to normalize data and try to run various resolutions to determine which one is good for clustering. However, once it comes to for loop sections, it shows me the clustering plot of resolution 0, but the rest was terminated with error saying that Error:…

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Visualize individual cell clusters colored by meta.data variable

Seurat: Visualize individual cell clusters colored by meta.data variable 0 Hello, I am analyzing a public scRNA dataset using Seurat. My goal is to observe variation inside individual cell clusters according to a condition (e.g. the diet) in a visual way using a dimensional reduction plot, e.g. observing sub-clusters of…

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Differential Expression Analysis using Bioconductor (RStudio) and GEO2R (GEO)

Hello everyone, I’ve been having the same question for a while now. I’m also conducting my own analysis of differential expression on a microarray dataset in R. However, the data is different from the results obtained using GEO2R. Here’s my line of code: my_id <- “GSE80178” gse <- getGEO(my_id, GSEMatrix…

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Mutational spectra are associated with bacterial niche

Bacteria exhibit diverse mutational spectra Using a specifically-developed open-source bioinformatic tool, MutTui (github.com/chrisruis/MutTui), we analysed whole genome sequence alignments and phylogenetic trees to reconstruct single base substitution (SBS) mutational spectra of 84 phylogenetic clades from 31 diverse bacterial species representing a broad range of phylogenetic diversity and replication sites (Figs. S1…

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slingshot analysis on PCA but visualization on UMAP

slingshot analysis on PCA but visualization on UMAP 1 Hi Bio-community, I am using slingshot for TI. I am wondering If I can use PCA as reducedDim argument in the slingshot function and for visualization the UMAP in embedCurves? Since I am getting biologically more reasonable results, if working in…

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Fasting-Mimicking Diet Drives Antitumor Immunity against Colorectal Cancer by Reducing IgA-Producing Cells | Cancer Research

Fasting-mimicking diet (FMD) is emerging as an effective dietary intervention with the potential to prolong life span in healthy people and boost antitumor immunity in patients with cancer. FMD refers to a medically designed fasting-like state that allows periodic consumption of a very-low-calorie and low-protein diet (1, 2). Compared with…

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Reproducible seurat clustering

Dear all fellows, What is the standard way for reproducible Seurat clustering in single cell? I have been trying to use set.seed function like library(tidyverse) library(Seurat) library(patchwork) set.seed(198752) However, once it comes to running the following script, I get new shape of cluster all the time I rerun it. How…

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Normalized data values very different from unnormalized counts in Seurat

Normalized data values very different from unnormalized counts in Seurat 0 I the sceasy R package to convert Burclaff et al.’s (2022) single-cell data (GSE185224) from scanpy H5AD data to a Seurat R object. My object’s UMAP looks similar to the authors, and I subsetted out “colon” samples. I then…

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Integration Seurat different healthy samples (fresh vs frozen)

Integration Seurat different healthy samples (fresh vs frozen) 0 Hi Bio-community, I am investigating a single cell dataset using the seurat workflow. In total I have 8 different samples, each from a different patient. 7 of them were frozen samples and S8 in the umap plot is the only fresh…

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How to ‘organize’ multiple umap/genes generates with Seurat `FeaturePlot`in a specific way

How to ‘organize’ multiple umap/genes generates with Seurat `FeaturePlot`in a specific way 1 Hi, Do you know how to ‘organize’ multiple umap generates with Seurat FeaturePlotin a specific way? For example organize 4 plots all all vertically or horizontally instead of having them organised as 2×2 or only plot_grid is…

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How to import filtered_tf_bc_matrix and add it to my anndata object?

Hello, I am analyzing some ATAC samples and I would like to add the motif information to my objects. So far I have imported my fragment files and clustered the cells. I would like to add the filtered_tf_bc_matrix information so I can do differential expression based on the motifs but…

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Using SAM for the Prediction of Segmentations on the Kaggle Football Player Segmentation Dataset

Welcome to the latest installment of our ongoing blog series where we highlight notebooks and datasets from the FiftyOne Examples GitHub repository. The fiftyone-examples repository contains over 30 notebooks that make it easy to try various computer vision workflows and explore their associated datasets. In this post, we take a…

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How to remove the default title to a DimPlot() splitted into two by group.by ?

How to remove the default title to a DimPlot() splitted into two by group.by ? 1 Hi, Is it is possible to remove the default title (in the pic below “stim”) to a DimPlot() which is splitted into two by group.by.? I want to generate the same type of plot/pannel…

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Rename of assays for SingleCellExperiment object in R

Rename of assays for SingleCellExperiment object in R 1 Hi, I would like to ask a question related to the renaming of assays for the SingleCellExperiment object in R. My data as below: cortex_sc class: SingleCellExperiment dim: 30535 6460 metadata(9): Integrated_colors category2_colors … pca umap assays(2): **X** logcounts rownames(30535): MIR1302-2HG…

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A spatial sequencing atlas of age-induced changes in the lung during influenza infection

Single-cell RNA sequencing reveals cellular heterogeneity among young and aged lungs post-influenza infection In order to investigate age-induced alterations in the host response to influenza A virus (IAV) infection, we infected groups of three young (16–18-week-old) and three aged (80–82-week-old) female C57Bl/6 mice intranasally with 50 PFU of the PR8…

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Plotting time series data after running natural splines regression in DESeq2.

Hello, I am running differential expression analysis on age-related changes in transcription using natural splines with DESeq2 like so: dds <- DESeqDataSetFromMatrix(countData = counts, colData = coldata, design = ~ ns(age_scaled, df = 3)) keep <- rowSums(counts(dds) >= 10) >= 3 dds <- dds[keep,] dds <- DESeq(dds, test=”LRT”, reduced =…

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Simulation of undiagnosed patients with novel genetic conditions

Simulated patient initialization We simulate patients for each of the 2134 diseases in Orphanet20 (orphadata.org, accessed October 29, 2019) that do not correspond to a group of clinically heterogeneous disorders (i.e., Orphanet’s “Category” classification31), have at least one associated phenotype, and have at least one causal gene. For Orphanet diseases…

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Mexican Biobank advances population and medical genomics of diverse ancestries

Encuesta Nacional de Salud 2000 Since 1988, Mexico has established periodical National Health Surveys (Encuesta Nacional de Salud (ENSA), originally conceived as National Nutrition Surveys) for surveillance of Mexican population-based nutrition and health metrics. In this study, we use data and samples collected from the survey carried out in 2000,…

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Uniting in-line imaging process analytical technology with machine learning to assess and predict cellular states of Chinese Hamster Ovary cells in monoclonal antibody (mAb) bioprocessing

Chinese Hamster Ovary (CHO) cells serve as the backbone of modern large-scale manufacturing of monoclonal antibodies. Key to this process is the usage of fed-batch cultures, where cells are grown from low to high cellular densities, go through a mAb production phase, and begin to die off. Despite CHO cells…

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Picking optimal resolution for single cell in seurat pipeline

Picking optimal resolution for single cell in seurat pipeline 1 Dear all fellow members, as I progressed into single cell analysis, one question that I would like to ask is how do we know the optimal resolution we should pick for our data as cluster will change once the resolution…

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Feature plot not applicable for RunTSNE object in seurat?

Feature plot not applicable for RunTSNE object in seurat? 1 Dear All, I visualized my cluster using tsne object (image attached) and would like to run FeaturePlot to examine the expression of particular gene, but it did not work for tsne object. I could only do it with UMAP. Any…

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Filter, Plot, and Explore with Seurat in RStudio

First thing’s first, we need to load the packages we will be using. In order to use any functions of a package, we must first call the library of that package. In your console (likely in the lower left corner of your RStudio window), run the following lines of code…

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The RNA velocity are opposite in ‘dynamical’ and ‘stochastic’ modes.

Hi When I run velocity using both ‘dynamical’ and ‘stochastic’ modes: import scvelo as scv import scanpy as sc scv.pp.moments(adata) scv.tl.velocity(adata, mode=”stochastic”) scv.tl.velocity_graph(adata) scv.pl.velocity_embedding_stream(adata, basis=”umap”, arrow_size = 1, density = 2, size = 50, arrow_style=”->”, color=”leiden_r1″, alpha = 0.2, dpi = 300, legend_loc=”on data”, integration_direction = ‘both’, arrow_color=”k”, figsize =…

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Integration of single-nuclei RNA-sequencing, spatial transcriptomics and histochemistry defines the complex microenvironment of NF1-associated plexiform neurofibromas | Acta Neuropathologica Communications

Single-nuclei RNA-sequencing analysis of NF1-associated plexiform neurofibroma reveals specific non-neoplastic and neoplastic cellular subpopulations Single-nuclei RNA-sequencing (snRNA-seq) was performed on 8 bulk frozen PN patient samples capturing approximately 4,000 nuclei per sample, a sufficient number of nuclei to provide adequate coverage to report the high levels of cellular heterogeneity found…

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Integration of single-nuclei RNA-sequencing, spatial transcriptomics and histochemistry defines the complex microenvironment of NF1-associated plexiform neurofibromas

doi: 10.1186/s40478-023-01639-1. Vladimir Amani  1   2 , Kent A Riemondy  3 , Rui Fu  4 , Andrea M Griesinger  5   6 , Enrique Grimaldo  5   6 , Graziella Ribeiro De Sousa  5   6 , Ahmed Gilani  7 , Molly Hemenway  6 , Nicholas K Foreman  5   6 , Andrew M Donson #  5   6…

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comparision of umap single cell

comparision of umap single cell 0 Dear Fellow, I’m currently learning to analyze single cell RNAseq and compare my result with the analysis by bioinformatician. We analyzed the same data of 9 individual patients from 10X. His UMAP looks nice, but mine looks a bit messy and aggregated together. I…

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Environment and taxonomy shape the genomic signature of prokaryotic extremophiles

Supervised machine learning analysis of the Temperature Dataset and the pH Dataset Supervised classification by taxonomy, environment category, and random label assignment Several supervised machine learning computational tests were performed to classify the Temperature Dataset and the pH Dataset, respectively, using (1) taxonomy labels (domain), (2) environment category labels, and…

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Integrated Seurat object change name of the two conditions

Integrated Seurat object change name of the two conditions 0 Hi, I have a scRNAseq integrated seurat object composed by my control and my treatment. On this object I did all the analysis and I have all the plots needed (umap etc). Now it has been asked to use different…

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Abnormal developmental trajectory and vulnerability to cardiac arrhythmias in tetralogy of Fallot with DiGeorge syndrome

Generation and characterisation of patient-specific hiPSCs and hiPSC-CMs hiPSC lines were established from two TOF-DG patients, two TOF-ND patients, and two healthy controls with pluripotency markers and germ layer markers verified (Supplementary Figs. 1 and 2). Whole genome sequencing confirmed, respectively, the presence and the absence of 22q11.2 deletion in the…

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Is there an easy to modify the subplot titles in DimPlot (Seurat)?

Is there an easy to modify the subplot titles in DimPlot (Seurat)? 3 Dear experts, When using DimPlot to plot the UMAP for the combined Seurat object, say it includes two groups, the combined object after the Dimplot will become one patchwork gg ggplot structure, while how to change each…

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A biobank of pediatric patient-derived-xenograft models in cancer precision medicine trial MAPPYACTS for relapsed and refractory tumors

Patient characteristics and PDX establishment Between February 2016 and July 2020, 787 pediatric, adolescent and young adult patients with recurrent or refractory malignancies were enrolled in the MAPPYACTS trial;2 756 (96%) patients and their parents consented to the optional ancillary study of preclinical model development (Fig. 1a). 744 patients had a…

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Single-cell screening of cerebral organoids to identify developmental defects in autism

In a recent study published in Nature, researchers develop the clustered regularly interspaced short palindromic repeats (CRISPR)-human organoids-single-cell ribonucleic acid (RNA) sequencing (CHOOSE) system to identify developmental brain defects in autism. Study: Single-cell brain organoid screening identifies developmental defects in autism. Image Credit: Yurchanka Siarhei / Shutterstock.com Diagnosing autism Autism spectrum disorder (ASD) is…

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Identification of co-diagnostic effect genes for aortic dissection and metabolic syndrome by multiple machine learning algorithms

Identification and functional enrichment analysis of common DEGs Batch effects had been eliminated with Rank-In in all samples from the AD combined dataset and GSE98895 dataset, as shown in Fig. 2A,B. The 3023 DEGs (1376 up- and 1647 down-regulated) were screened between AD and control subjects using the ‘limma’ package in…

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Converting scMultiome data to loom using SEURAT

I’m using scMultiom data with the CCAF tool to predict cell cycle phases. CCAF : github.com/plaisier-lab/ccAF CCAF requires a loom file as input. I converted the output h5 file from cellranger-arc and atac_fragment.tsv.gz to a loom file using Seurat’s code. library(Seurat) library(Signac) library(EnsDb.Hsapiens.v86) library(dplyr) library(ggplot2) library(SeuratDisk) inputdata.10x <- Read10X_h5(“D:/Halima’s Data/Thesis_2/1_GD428_21136_Hu_REH_Parental/outs/filtered_feature_bc_matrix.h5”)…

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Help with scvi error

Help with scvi error 0 Hi all, I could not find this error after searching, would you please have a suggestion? I paste the line that show the error message to make the post not too long. I appreciate it! sc.pp.neighbors(adata, use_rep = ‘X_scVI’) sc.tl.umap(adata) sc.tl.leiden(adata, resolution = 0.5) RuntimeError…

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UMAP graph using DimPlot pre/post integration

UMAP graph using DimPlot pre/post integration 1 Hello all, I have a seurat object containing 3 different samples. Before integration with harmony, I can run: pbmc_harmony <- NormalizeData(pbmc_harmony, verbose = F) pbmc_harmony <- FindVariableFeatures(pbmc_harmony, selection.method = “vst”, nfeatures = 2000, verbose = F) pbmc_harmony <- ScaleData(pbmc_harmony, verbose = F) pbmc_harmony…

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Help with error scanpy

Hi all, I try to do annotation for single cell using scanpy and got this error that I didn’t found on the internet:Would you please have a suggestion? Code is adapt from github.com/bnsreenu/python_for_microscopists/blob/master/326_Cell_type_annotation_for_single_cell_RNA_seq_data%E2%80%8B.ipynb Thank you so much! sc.pl.umap(adata) ————————————————————————— AttributeError Traceback (most recent call last) Input In [34], in <cell…

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Cluster annotation in single cell

Cluster annotation in single cell 0 Dear Fellows, In Single cell, once we perform a clustering, for example, “umap”, which generate X number of clusters. Next is to perform annotation for cluster, which can be done by looking at differentially expressed genes within each cluster. if we get DEG within…

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Comparative single-cell transcriptomic analysis of primate brains highlights human-specific regulatory evolution

Consensus MTG taxonomy across primates The BRAIN Initiative Cell Census Network26 generated high-resolution transcriptomic maps of the MTG in human, chimpanzee, gorilla, macaque and marmoset by applying single-nucleus transcriptomic (snRNA-seq) assays to samples isolated from between three and seven donor brains in each species (plate-based SMART-seq v4 (SSv4) for great…

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Blaine Bateman, EAF on LinkedIn: [Product Launch] Introducing Kaggle Models | Kaggle

I like to promote the power of embeddings in ML/AI. In particular, I find UMAP very useful to generate meaningful embeddings as features for models. Parametric UMAP trains a neural network to learn the relation between data and embeddings, using the same objective function as UMAP. You can define custom…

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TimeTalk uses single-cell RNA-seq datasets to decipher cell-cell communication during early embryo development

Curation of early-embryo development single-cell RNA-seq data sets for studying cell-cell communication To identify and study eLRs, we collected public early embryo development scRNA-seq datasets from the mouse MII-oocyte stage to the late blastocyst stage to ensure that scRNA-seq datasets represented every stage of early embryo development. In addition, to…

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Multiplexed transcriptomic profiling of the fate of human CAR T cells in vivo via genetic barcoding with shielded small nucleotides

Wagner, A., Regev, A. & Yosef, N. Revealing the vectors of cellular identity with single-cell genomics. Nat. Biotechnol. 34, 1145–1160 (2016). Article  CAS  PubMed  PubMed Central  Google Scholar  Gehring, J., Hwee Park, J., Chen, S., Thomson, M. & Pachter, L. Highly multiplexed single-cell RNA-seq by DNA oligonucleotide tagging of cellular…

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Question about umap using different numbers of pca components as initialization

Question about umap using different numbers of pca components as initialization 0 I am new to the scRNA-seq field and I have been doing some experiments of visualization of UMAP using different numbers of PCA components for initialization. The process involves projecting scRNA-seq data (count matrix) onto various numbers of…

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Help with weighted nearest neighbor analysis

Help with weighted nearest neighbor analysis 0 Hi all, I try to use this vignette on my single cell multiome data and not sure how to get the gene to run the function below. The data from endothelial cell and fibroblast. Would you please have a suggestion? I appreciate your…

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Solved Ignore tasks 1.1,1.2,1.3. Only do task “## **Group 3

Ignore tasks 1.1,1.2,1.3. Only do task “## **Group 3 (D Tasks) Analyse the learned representations**” With this group of tasks, you are going to build a neural network for the image classification task. You will train the model on the diabetes prediction dataset. www.kaggle.com/datasets/iammustafatz/diabetes-prediction-dataset Task 1.1 Understanding the data (weight…

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Co-expression of markers in single cells using scanpy

Co-expression of markers in single cells using scanpy 0 Hello, I am new to the world of single cell analysis, but scanpy has been useful for my analyses so far. However, I want some way to visualise the co-expression of two marker genes in single cells on a UMAP. I…

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Dynamic thresholding and tissue dissociation optimization for CITE-seq identifies differential surface protein abundance in metastatic melanoma

Workflow overview CITE-seq and cell hashing were performed on liquid and solid tissue biopsies (Fig. 1a, b). Experimentally, cells from 17 samples (Supplementary Data 2) were hashed and stained with a panel of 97 antibodies (Supplementary Data 2) covering key as well as exploratory immuno-oncology markers resulting in 57,261 cells after preprocessing and…

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Error in h(simpleError(msg, call)) in monocle2

Error in h(simpleError(msg, call)) in monocle2 0 Want to run monocle2 for a single cell RNAseq data processed using Seurat, but encountering following problem. library(monocle) Seurat An object of class Seurat 41445 features across 55683 samples within 1 assay Active assay: RNA (41445 features, 1850 variable features) 4 dimensional reductions…

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How to preprocess and visualize beautifully scRNA-seq with omicverse?

Omicverse is the fundamental package for multi omics included bulk and single cell RNA-seq analysis with Python. To get started with omicverse, check out the Installation and Tutorials. For more details about the omicverse framework, please check out our publication. The count table, a numeric matrix of genes\u2009\u00d7\u2009cells, is the…

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Cas9-mediated knockout of Ndrg2 enhances the regenerative potential of dendritic cells for wound healing

Ndrg2 expression is reduced in tolerogenic DCs To identify potential targets for gene editing in DCs, we compared transcriptomic profiles of treatment induced tolerogenic DCs, which confer a variety of clinical benefits11,12,13,14,15,16,17 with untreated DCs. Bone marrow-derived DCs were cultivated from wild-type (WT) mice (C57/BL6) according to standard protocols25. Vitamin…

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Large-scale analysis of flavivirus sequences, with no unknowns, in Aedes aegypti whole-genome DNA sequence data | Parasites and vectors

Spadar A, Phelan JE, Benavente ED, Campos M, Gomez LF, Mohareb F, et al. Flavivirus integration Aedes aegypti Limited and highly conserved across samples from different geographic regions, unlike integration Aedes albopictus. vectors of parasites. 2021; 14 (1): 332. Palatini U, Contreras CA, Gasmi L, Bonizzoni M. Endogenous viral elements…

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Large-scale reference-free analysis of flavivirus sequences in Aedes aegypti whole-genome DNA sequencing data

Spadar A, Phelan JE, Benavente ED, Campos M, Gomez LF, Mohareb F, et al. Flavivirus integrations in Aedes aegypti are limited and highly conserved across samples from different geographic regions in contrast to integrations in Aedes albopictus. Parasite vectors. 2021;14(1):332. Palatini U, Contreras CA, Gasmi L, Bonizzoni M. Endogenous viral…

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Large-scale reference-free analysis of flavivirus sequences in Aedes aegypti whole genome DNA sequencing data | Parasites & Vectors

Spadar A, Phelan JE, Benavente ED, Campos M, Gomez LF, Mohareb F, et al. Flavivirus integrations in Aedes aegypti are limited and highly conserved across samples from different geographic regions unlike integrations in Aedes albopictus. Parasit Vectors. 2021;14(1):332. Palatini U, Contreras CA, Gasmi L, Bonizzoni M. Endogenous viral elements in…

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Multiparametric senescent cell phenotyping reveals targets of senolytic therapy in the aged murine skeleton

Development and validation of a senescence CyTOF antibody panel We constructed and validated a comprehensive CyTOF antibody panel to include markers for both cell identity and senescent phenotype (Table 1). A defining characteristic of senescent cells is expression of cell cycle inhibitors, in particular p16 or p2129, so we carefully validated…

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Senior Bioinformatics Scientist – Enhanc3D Genomics

VACANCY – Senior Bioinformatics Scientist About Enhanc3D Genomics Enhanc3D Genomics is a functional genomics spinout company from the Babraham Institute (Cambridge, UK) leveraging a disruptive technology to profile interactions of gene promotors with distal DNA regulatory elements that allow unbiased allocation of enhancers to their target genes across the genome….

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A universal tool for predicting differentially active features in single-cell and spatial genomics data

singleCellHaystack methodology For a detailed description of the original singleCellHaystack implementation (version 0.3.2) we refer to Vandenbon and Diez19. In brief, singleCellHaystack uses the distribution of cells inside an input space to predict DAFs. First, it infers a reference distribution \(Q\) of all cells in the space by estimating the…

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How to specify which resolution I want to be plotted in the UMAP?

How to specify which resolution I want to be plotted in the UMAP? 0 Hi, Maybe is it a stupid question but I integrated two dataset with harmony and like this post I tried different resolutions. How can I specify which resolution I want to be plotted? Dimplot show only…

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Set up label.color with the same colors as the cluster colors in Seurat DimPlot() ?

Set up label.color with the same colors as the cluster colors in Seurat DimPlot() ? 1 Hello, I want to show on my UMAP, using the DimPlot() function, the same colors on the text labels as the cluster colors. If I set up the same colors in the same order…

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new visualization method for dimension reduction technique

new visualization method for dimension reduction technique 0 Hello, I heard that there is a new dimension reduction technique that for visualization, and it better than UMAP and TSNE. However, anyone heard about this new technique? And how is it performance? ThanksAndy dimension-reduction • 38 views • link updated 40…

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Cluster/group samples based on scRNA data

Forum:Cluster/group samples based on scRNA data 0 Hi all, I have ~50 samples with each being profilied by scRNA. By UMAP of each individual sample, I can clearly see 3-4 distinct patterns among these samples. Now what is the appropriate way for me to group these samples according to their…

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Error while mapping data to reference using Symphony

Error while mapping data to reference using Symphony 0 Hello everyone, I am trying to reproduce this tutorial using the data I have. Symphony tutorial However, when I am mapping the query to the reference, query = mapQuery(query_exp, query_metadata, reference, do_normalize = TRUE, do_umap = TRUE) I get an error…

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GPX4 is a key ferroptosis biomarker and correlated with immune cell populations and immune checkpoints in childhood sepsis

Identification of DE-FRGs in sepsis After the debatch normalization treatment of GSE26378 and GSE26440 (Fig. 2A, Supplementary Figure 1), the differential expression analysis was performed, including 20,021 significantly differentially expressed genes, including 12,758 upregulated genes and 7,263 downregulated genes. log2FC ≥ 1, adjusted P < 0.05 (Fig. 2B). To explore differentially expressed FRG in sepsis, we extracted…

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Anatomical and molecular characterization of parvalbumin-cholecystokinin co-expressing inhibitory interneurons: implications for neuropsychiatric conditions

Genetic targeting of CCK+ interneurons restricted by the Dlx5/6 driver line in mouse hippocampus and neocortex CCK isoforms and their preprohormone can be expressed in excitatory neurons in addition to GABAergic interneurons [28]. In order to target CCK+ inhibitory interneurons only, we employed an intersectional genetic strategy by simultaneous co-expression…

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How to plot VDJ clonotyping data in UMAP of Seurat object using Immunarch

How to plot VDJ clonotyping data in UMAP of Seurat object using Immunarch 0 Hello, I’m new to Immunarch and I’m trying to plot VDJ information on a Seurat UMAP plot. However, I’m having trouble finding any tutorials or vignettes related to this topic, apart from those mentioning the select_clusters…

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How to label clusters from a UMAP

How to label clusters from a UMAP 0 So this is a broad question that I was hoping someone could shed some light on. I have a Visium tissue data set which I’ve clustered using scanpy, and for each tissue slice I usually get 5 or 6 resulting clusters. I…

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Staff Bioinformatics Scientist – San Leandro

Bioinformatics Scientist We are seeking a highly motivated and skilled Bioinformatics Scientist to join our R&D team. The successful candidate will be integral to our genomics research efforts. This role requires expertise building pipelines from sequencer output to feature generation from both RNA and DNA sources. The candidate should have…

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Bioconductor – ChromSCape

DOI: 10.18129/B9.bioc.ChromSCape     This package is for version 3.15 of Bioconductor; for the stable, up-to-date release version, see ChromSCape. Analysis of single-cell epigenomics datasets with a Shiny App Bioconductor version: 3.15 ChromSCape – Chromatin landscape profiling for Single Cells – is a ready-to-launch user-friendly Shiny Application for the analysis…

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scRNA seq analysis – how to label cell types from clusters

2 hours ago bioinformatics &utrif; 10 Hello, I have followed this tutorial/workflow and managed to create a UMAP plot with labelled clusters (1-12 using the patient 1 of GSE162454 dataset from NCBI): holab-hku.github.io/Fundamental-scRNA/downstream.html#run-non-linear-dimensional-reduction-umaptsne However, the tutorial did not show how to create a UMAP plot with cell types labelled using…

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Small RNA sequencing of field Culex mosquitoes identifies patterns of viral infection and the mosquito immune response

Ronca, S. E., Ruff, J. C. & Murray, K. O. A 20-year historical review of west nile virus since its initial emergence in north america: Has west nile virus become a neglected tropical disease?. PLoS Negl. Trop. Dis. 15, 1–20 (2021). Article  Google Scholar  Diaz, A., Coffey, L. L., Burkett-Cadena,…

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How to add VDJ clonotyping data to Seurat object of scRNA-seq

How to add VDJ clonotyping data to Seurat object of scRNA-seq 0 I have performed CITE-seq (ADT, GEX, TCR) in 20 PBMC samples, consisting of responders and non-responders. By following Seurat tutorial, I performed standard pre-processing process, merging seurat object, integration, and drew the UMAP and compared the freq. of…

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Should primary tumor RNA-Seq match their derived cell lines and PDXs? And which dimensionality reduction method should I use?

Should primary tumor RNA-Seq match their derived cell lines and PDXs? And which dimensionality reduction method should I use? 0 I have processed a bunch of RNA-Seq data coming from patient primary tumours and their respective established cell lines and PDXs. My question is, should the cell lines/PDXs cluster together…

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Integration of bulk RNA sequencing data and single-cell RNA sequencing analysis on the heterogeneity in patients with colorectal cancer

Bao X, Shi R, Zhao T, Wang Y, Anastasov N, Rosemann M et al (2021) Integrated analysis of single-cell RNA-seq and bulk RNA-seq unravels tumour heterogeneity plus M2-like tumour-associated macrophage infiltration and aggressiveness in TNBC. Cancer Immunol Immunother 70(1):189–202 Article  CAS  PubMed  Google Scholar  Becht E, McInnes L, Healy J,…

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Y chromosome loss in cancer drives growth by evasion of adaptive immunity

Caceres, A., Jene, A., Esko, T., Perez-Jurado, L. A. & Gonzalez, J. R. Extreme downregulation of chromosome Y and cancer risk in men. J. Natl Cancer Inst. 112, 913–920 (2020). Article  PubMed  PubMed Central  Google Scholar  Kido, T. & Lau, Y. F. Roles of the Y chromosome genes in human…

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Sex specific molecular networks and key drivers of Alzheimer’s disease | Molecular Neurodegeneration

Differential gene expression profiles of female and male AD versus control The numbers of differentially expressed genes (DEGs) identified from different comparisons (AD versus normal aging control subjects; females versus males) were shown in Fig. 1A and Supplemental Fig. 1A. In the PHG region, DEG signatures generated from three comparison groups…

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Multiplexed single-cell 3D spatial gene expression analysis in plant tissue using PHYTOMap

Sample preparation Arabidopsis thaliana accession Col-0 seeds (hereafter Arabidopsis) were sown on square plates containing Linsmaier and Skoog medium (Caisson Labs, catalogue no. LSP03) with 0.8% sucrose solidified with 1% agar (Caisson Labs, catalogue no. A038). Plates were kept vertically for 5 days in a growth chamber under an 8:16 h light/dark…

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A single cell transcriptomic fingerprint of stressed premature, imbalanced differentiation of embryonic stem cells

Cultured naïve pluripotent ESC differentiate into first lineage, XEN or second lineage, formative pluripotency. Hyperosmotic stress (sorbitol), like retinoic acid, decreases naive pluripotency and increases XEN in two ESC lines, as reported by bulk and scRNAseq, analyzed by UMAP. Sorbitol overrides pluripotency in two ESC lines as reported by bulk…

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how to ensure that embedding for the new data is initialized based on the embedding of the existing data in UMAP?

how to ensure that embedding for the new data is initialized based on the embedding of the existing data in UMAP? 0 Hello all, I have a merged dataset of mouse-human and by applying umap on the data I get some shared cluster of mouse-human. Now I would like to…

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Why is Babesia not killed by artemisinin like Plasmodium? | Parasites & Vectors

Babesia genomes lack enzymes of the complete haem synthesis system as compared to Plasmodium genomes Babesia genomes comprise four chromosomes, and range in size from 6 to 15 Mb [e.g. Babesia microti (6.44 Mb), Babesia bovis (8.18 Mb), Babesia bigemina (12.84 Mb), Babesia ovata (14.45 Mb), Babesia ovis (8.38 Mb) and Babesia divergens (9.65 Mb) (Additional file…

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Team identifies IL-17 protein as key factor in skin aging

Dermal cell characterization by 10X scRNA-seq. a, Workflow used to obtain dermal cells of adult and aged mouse back skin. Single-cell suspensions were enriched separately for EpCAM–CD45– and CD45+ cells by FACS. Transcriptomes of sorted single cells were then analyzed by 10X scRNA-seq. For CD45+ cells, n = 7 mice for the adult…

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New study suggests simple test could detect breast and ovarian cancer risk without genetic sequencing

Development of the BRCA-mt signature. UMAP representation of BRCA-mt and BRCA-wt samples from all evaluated cohorts without (a) and after (b) batch adjustment (N = 653). Volcano plots showing differentially expressed miRNAs between BRCA-mutated and wild-type samples without (c) and after (d) batch adjustment (N = 521); red markings represent miRNAs with P < 0.01 and FC > 1.5…

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Tox4 regulates transcriptional elongation and reinitiation during murine T cell development

Pan-hematopoietic Tox4 deletion reduces number of multipotential progenitors and impairs T cell development To understand the role of TOX4 in development, we generated Tox4 conditional knockout mice by the CRISPR-Cas9 methodology, and two loxP sites in the same orientation were inserted upstream and downstream of exons 4–6, respectively (Supplementary Fig. 1a). Considering…

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